Industry

Sep

2021

Carolin Dirks

Born in Steinfurt, Germany • Studied Maths at the University of Münster, Germany • Highest Degree Doctorate in Maths • Lives in Steinfurt, Germany • Occupation Software Developer at LVM Versicherung (insurance company)

When I started studying maths, I was frequently asked what I was planning to do after graduating. “Who wants to hire a mathematician? Do you want to end up in a boring job working in the financial sector or in an insurance?” Of course, like most of my fellow students, I did not have a satisfying answer to these questions. Today, after several years of studying and struggling with lots of formulas, proofs and theorems, I have learned two very important lessons: First, that there are thousands of opportunities in very different branches of industry and academia a mathematician can take, and second, that having an inspiring and exciting job and working for an insurance is not a contradiction.

And what came next finally took me to the decision to stay with maths for the rest of my life: I realised that I was not the worst student (though not the best either), and I was fascinated by the clarity and pure logic of mathematical problems, forming a huge contrast to the, in my opinion, very unclear analysis of poems and classic literature (sorry to those who would disagree with this point).

In my experience, studying maths is a decision made out of the interest for logical structures, for clarity and puzzles, but not for a particular future job. Unlike many others, the presence of this interest was not clear to me until I reached the last years of high school. Thus I cannot claim that I had always been fascinated by mathematics, though I was never a bad student, my interests lay elsewhere – largely in learning languages, which I still try to spend some time with beside my current job. This changed due to a sudden and, at least in retrospect, very fortunate coincidence: When I had to choose my advanced courses for my last two years at school (every German academic high school student has to decide for two), due to organisational reasons I ended up in the advanced maths class. For a few weeks, I was quite depressed, being sure that I would be the most stupid student next to all those maths geniuses. And what came next finally took me to the decision to stay with maths for the rest of my life: I realised that I was not the worst student (though not the best either), and I was fascinated by the clarity and pure logic of mathematical problems, forming a huge contrast to the, in my opinion, very unclear analysis of poems and classic literature (sorry to those who would disagree with this point). Out of this fascination I finally made the decision to study maths, without having a specific career aspiration and even without having any idea about possible careers.

Although in my opinion, society made great progress in overcoming gender-specific obstacles, I also made the experience that women interested in computer stuff are still a bit unusual. This caused me to be suspicious – would I be good enough, would I be able to establish myself in this branch and would I find a job as a mathematician?

At the university, I fought my way through the first few semesters without a specific plan – but instead with lots of very close new friends with the same mind-set, since studying maths is not least a matter of team work. In my fourth semester, I first encountered the field of numerical mathematics, which, roughly speaking, can be explained as the area of intersection between maths and computer science. I realised how closely related these two fields are: Computer science can be used to solve lots of mathematical problems, while every computer program uses the “language” of mathematics and logics. I was fascinated by the variety of applications and decided to concentrate on this field in my further studies. And slowly, very hesitantly in the beginning, I started thinking that maybe I could become a software developer. Hesitantly because up to this point, I never had any points of contact with computer science in my life, not because I was not interested, but simply because it never came to my mind. Although in my opinion, society made great progress in overcoming gender-specific obstacles, I also made the experience that women interested in computer stuff are still a bit unusual. This caused me to be suspicious – would I be good enough, would I be able to establish myself in this branch and would I find a job as a mathematician? To find the answers to all these questions, I needed to try it out – so I tried, and it was worth it.

Before this rough idea could emerge to a specific plan, a few more years had to pass by. After graduating, I was still insecure about what I wanted to be. Not only, but also not at least in order to postpone a “final” decision, I decided to stay at the university and do a PhD, despite again fighting with my doubts of being good enough. This turned out to be a great idea – I was now able to contribute my own ideas and, in this way, further develop my interests and strengths, all the time attended by a great, supporting and understanding scientist. And although I was for sure not the best student (thanks to my supervisor’s patience at this point), I finally made it, having learned one of the most important lessons in life: You can do it if you really try.

At this point in my life, I knew what I wanted: To use my mathematical logical knowledge in combination with my (at this point, quite acceptable) programming skills to contribute to something “tangible”, something someone could really make use of […].

After finishing my PhD (and now, with a particular plan, namely to become a software developer), I applied for my first job outside of academia. At this point in my life, I knew what I wanted: To use my mathematical logical knowledge in combination with my (at this point, quite acceptable) programming skills to contribute to something “tangible”, something someone could really make use of (sadly this is something missed by many maths students during their studies). The explicit sector was not important for me, since I found for myself that those really deep and specific programming problems are fascinating no matter if the application behind is just a web-enabled water boiler. So I thought, why not an insurance company? The job advertisement sounded very interesting. The company was looking for developers for a completely new contract software, which would be used by the insurance agencies all over Germany. This promised not to be the boring insurance job every first-year maths student is afraid of, so I took the chance. Retrospectively, I am very happy about the path I took, and proud of having had the courage to take it, regardless of my doubts and fears of not being good enough. Although this is something several maths students have in common, most of my former fellow students also share the ability of tenacity, they do not give up easily, but make their way and realise that it works – in the end, the struggle was worth it and I would strongly recommend to just give it a try.

Sep

2021

Maylin Wartenberg

Born in Braunschweig, Germany • Studied Math (diploma) at the Technical University in Braunschweig, Germany • Highest Degree Doctorate in Math (Dr. rer. nat.) • Lives in Meine, Germany • Occupation Professor at the Hochschule Hannover – University of Applied Sciences and Arts, Department of Business Information Systems, Field of Data Science

Analytical thinking has always been easy for me. Therefore, I enjoyed the rules and patterns that occur in math from early on. Luckily, I recovered quickly after the German high school greeted me with the minimum pass mark “adequate” in the first two math exams in 7^th grade. In 9^th and 10^th grade, we had a very strict “old school” teacher who left a lasting impression. We always had to stand up to greet him, and if you used a swear word in class, you had to wash the glasses in the chemistry room during the next break. He was strict, but he liked me and I learned a lot. In 11^th grade I spent a high school year in the US and after this year I wanted to take math as one of my advanced courses. That was a tough decision because all I did at the American high school was statistics whereas in Germany everyone had started with curve sketching. After my return to Germany, the first exam in 12^th grade was about this topic. I didn’t know anything about it and I had 6 weeks of summer break to study. A former very kind teacher helped me with the material and I studied by myself and achieved a good mark. That was a major milestone to my decision to study math, since I was able to teach myself the topics of almost a whole school year. But I still wasn’t sure. Math or psychology?

After all the ups and downs you typically encounter during this phase – 3 years for me – I finished my doctoral thesis in math (graph theory) two weeks before my first daughter was born.

Both sounded very attractive to my 19-year-old self. The plans to move to Braunschweig with two of my friends were already settled and I finally chose math because it was giving me a wider range of options on what future opportunities to follow – because I had no clue what to do after my studies at that point. In the beginning we were quite a few students, but in the end only 4 of us were left in pure math – 25% women 😉. I chose most of my courses in abstract math – algebra, combinatorics – and did as little applied math as possible. I really enjoyed the study of group and ring structures and the book Algebra by Serge Lang was always by my side. I already dreamed of becoming a professor myself.

Yet, in the end, the question what to do with all the knowledge I gained crept more and more into my consciousness. That is why I didn’t pursue a strictly academic career, nevertheless I still wanted to secure the option, and chose a PHD position in business at Bosch (formerly Blaupunkt) in Hildesheim. No more group and ring theory, suddenly I had to write code in C++ for algorithms in navigation systems. I had avoided any computer science so far, thus, I was thrown in at the deep end. But I never regretted this step because I discovered that coding is not all at all as difficult as I thought – after all it’s logical – and I learned a lot about working in a bigger company. After all the ups and downs you typically encounter during this phase – 3 years for me – I finished my doctoral thesis in math (graph theory) two weeks before my first daughter was born.

I found the fitting position where I can combine my passion for analytical thinking, my academic background, and my work experience (…).

I stayed home with her and somehow managed the defence of my doctoral thesies with a 5-month-old baby and still deprived of decent sleep. After 8 or 9 months at home, my brain started asking to be challenged again, and I began to apply for jobs in industry. As a young mother I wanted to start part time, but as a woman holding a doctorate in mathematics that was not as easy to get as I hoped. After a long search, including several offers with 40 hours and more, I was finally rewarded by starting a job at VW Financial Services. My one-year-old daughter was able to stay at the company’s own childcare facility and I started with 27 hours a week as a systems analyst in the business intelligence department in IT. In almost 10 years I made my way from analyst, to project lead, to team lead all the way to head of two sub-departments and got enrolled in the management trainee program – most of this in part time including a maternity leave when I had my second daughter in between. Then, suddenly, another option which had gotten a little out of sight but was still a silent dream popped back in.

And that is my way to my current position as a professor in business computing, especially data science. I found the fitting position where I can combine my passion for analytical thinking, my academic background, and my work experience – all of that with the advantage of being my own boss, still doing interesting projects with different companies, giving talks about AI for lay audiences (schools, senior clubs, …), and guiding young people on part of their own story.

Jul

2021

Natasha Karp

Born in United Kingdom • Birth year 1974 • Studied Biochemistry at Warwick University in United Kingdom • Highest Degree PhD in Chemistry from University of London • Lives in Cambridge, United Kingdom • Occupation Director Biostatistics at AstraZeneca

I really struggled at school in the early years, particularly with reading and writing; but then when I was around 12, it started to make sense. I was formally diagnosed as being dyslexic when I went to university, I guess when I was 12 things clicked into place as I found my strategies to get round my dyslexia. Those early years of struggling and being in bottom sets has left me with feelings of doubt but also a drive to prove people wrong. At 16, I selected mathematics with statistics, biology and chemistry as my specialist subjects and got the highest grades possible. I really enjoyed statistics and mathematics, and used to do extra work for fun. However, it was taught as a theoretical subject and I had no sense of what you could do with it. I also had no role models; I am the only person in my family to graduate from university. If you were a clever woman, you became a teacher or a doctor. Being a doctor didn’t appeal, so teaching became the ambition and I decided to study biochemistry with a year in industry at Warwick University and graduated with a first-class degree.

After I conducted some experiments, I felt the mathematical techniques used to make decisions were poor. Consequently, I started studying statistics (…).

I really enjoyed my year in industry, where I learnt the fundamentals of research, but after years of conditioning that my path was to be a teacher, I then trained as a secondary school teacher. After a couple of years teaching, I realised that I didn’t feel satisfied intellectually. I was working hard but didn’t feel I was growing. I decided to return to science and was offered a role back with the industrial placement company who sponsored me to complete a PhD in partnership with Imperial College, London. Unfortunately, the company folded but I just managed to complete my PhD. My confidence as a scientist felt low, I felt I had snuck in my PhD and I decided to work in academia to prove myself and joined the Cambridge Centre for Proteomics as a post-doc. I was very lucky and given a lot of freedom. After I conducted some experiments, I felt the mathematical techniques used to make decisions were poor. Consequently, I started studying statistics and writing papers exploring experimental design and data analysis for proteomic experiments. I was flying high and had 12 publications but then my first son was born and he was very poorly and I had to prioritise the family. I found a part-time job as a biostatistician with the Wellcome Trust Sanger Institute supporting in vivo research. It felt like I was starting again but I could meet my family needs and keep working. Over time, my son got better. The new environment gave me new opportunities; for example, I spent some time with database experts who helped me learn to code. I started publishing again in data analysis and experimental design for in vivo research. There wasn’t permanent funding in academia for this type of role so I applied to AstraZeneca, who had just relocated to Cambridge, as a statistician.

I feel my dyslexia is a strength, as it helps me see the bigger picture, connect ideas and be a better manager.

What am I doing now? I now lead a team of statisticians for AstraZeneca supporting preclinical research. I still work part-time (80%) to meet my family commitments. The work is very varied and we have the opportunity to make a big impact. We jump into projects, assist the scientists, enable their research and then jump to the next project. I find it surreal that I, a self-taught statistician, lead these amazing statisticians. I feel my dyslexia is a strength as it helps me see the bigger picture, connect ideas and be a better manager. As a dyslexic woman who has an unusual career path I bring diversity to the leadership element of my role. I also give lectures around the world on my research topics of interest and get the opportunity to work outside of AstraZeneca on working groups exploring topics such as sex bias or reproducibility. I love my job. It is applied statistics having impact.

As an individual with imposter syndrome, you have to recognise your voice of doubt but not let it control you.

My career path has had many twists and turns. That is real life. There are benefits, I have more experience to draw upon. I feel my journey shows there isn’t one path that is right for you. You should be open to opportunities and change. Change is positive. You do have to be prepared to take risks. As an individual with imposter syndrome, you have to recognise your voice of doubt but not let it control you. From the perspective of maths, data is everywhere, being good with data is such a strength. You don’t have to be a theoretical expert to add value and have impact. Enjoy your journey but don’t expect to know exactly where you are going and keep growing and challenging yourself.

Jun

2021

Paola Console

Born in Taranto, Italy • Birth year 1983 • Studied Mathematics at Università del Salento in Lecce, Italy – PhD at Université de Genève • Highest Degree PhD in Mathematics • Lives in Rome, Italy • Occupation Data Scientist at Enel

I was never good at math until high school. When I was a child, I loved spending my time reading and writing rhyming poems, so everyone in my family was sure my path would have had something to do with liberal arts. For this reason, they were really surprised (and probably worried) to hear I decided to start scientific studies in high school: for me it was a challenge, but I thought that by doing this I would have had a more complete education. There, I met a teacher who changed my life by starting to show math to me as a sequence of logical steps. I began finding it funny, logical, and telling everybody that to me, doing math exercises was comparable to playing crosswords.

After high school, it was logical for me to then start my studies in math in academia, with the idea to become a teacher. But in the end, I decided to complete my studies with a PhD in numerical analysis in Geneva, where I could also study different languages and meet people with different stories and backgrounds.

I really missed my country, my habits, my family, my friends, and therefore coming back home was a fundamental step to being happy in my life.

All the experiences I had while pursuing my PhD made me realize that I loved studying math, but that I prefer to apply it rather than develop new methods and proofs and, furthermore, that living in Italy was fundamental to me: I really missed my country, my habits, my family, my friends, and therefore coming back home was a fundamental step to being happy in life. I then decided to accept a postdoc position in neuroscience in Rome. I loved this job, but it was always meant to be a smooth transition towards the corporate world, where I would start to apply what I love to something more concrete by learning about machine learning and data science.

This experience helped me greatly in landing my current job, about six months after the end of my postdoc. I now work as a data scientist at Enel, one of the biggest private renewable energy companies in the world, in a huge group of data scientists that supports all the businesses and internal service functions, like procurement, in the company. My first projects consisted in applying machine learning techniques to detect faults in power plants, and I was very happy to finally see a real-world application for all my studies. Then I started to develop algorithms for the procurement field and now my main activity is undertaking a huge initiative to forecast the company’s income statement to support management decisions.

For all these reasons, when I think about my path, I am very happy about it, because it seems like I could, in the end, integrate all the different souls I had in my life (…)

What I really love about my current job is that it is based on applying math to the real world, but it is also really focused on relationships. Besides the modeling activities we carry out, I am also coordinating a small group of colleagues and I am involved in many other activities to spread data culture throughout the company with education and communication projects. One of the projects I am most proud of is the creation and the organization of an upskilling program called “Data School”, in which my team provides courses on topics related to data to colleagues of all areas. I think that engaging with people on topics related to data is a fundamental step to collaborate with them and support the data-driven transformation that is the main mission of my team.

For all these reasons, when I think about my path, I am very happy about it, because it seems like I could, in the end, integrate all the different souls I had in my life: the little girl writing poems, the student that wanted to be a teacher, and the rigorous mathematician.

Jun

2021

Marianne Freiberger

Born in Münster, Germany • Birth year 1972 • Studied Pure Mathematics at Queen Mary, University of London • Highest Degree PhD in Mathematics from Queen Mary, University of London • Lives in London, UK • Occupation Editor of Plus magazine (http://plus.maths.org)

I first became interested in maths when I learnt about the epsilon/delta definition of a limit at school. The fact that something as intuitive as a limit could be expressed so precisely in symbols blew my mind. Despite that interest, I didn’t really plan on studying maths at university. The reason I did was that I had moved to the UK from Germany after school and, when I finally decided to do a degree, thought my English wasn’t up to studying a more wordy subject (which is ironic given that I am now a writer).

I enjoyed my BSc, but by the end of it still didn’t think that maths would be part of my future. I spent a year working in all sorts of jobs and travelling, until a book by Ian Stewart re-ignited my passion. I applied for a PhD place with Shaun Bullett at Queen Mary, University of London, where I spent the next few years studying and researching holomorphic dynamics (which involves things like Julia sets and the Mandelbrot set). Shaun was a great supervisor who safely got me through my PhD (can’t have been easy!) and enabled me to stay on for another three years as a postdoc.

Because I’d been interested in science communication for a while, I applied for a maternity cover job at Plus magazine

Finding the next postdoc proved tricky and my heart wasn’t really in it. I didn’t want my life to revolve around my job, which as a postdoc is something you usually have to accept, and wasn’t sure I was a good enough mathematician. (Whether the latter was true or just down to lacking confidence — a notoriously female affliction— I still don’t know.) But it all turned out for the best: because I’d been interested in science communication for a while, I applied for a maternity cover job at Plus magazine. That was in 2005 and I am still at Plus now, co-editing along with my good friend and colleague Rachel Thomas.

Plus is a free online magazine about all aspects of maths, aimed at a general audience. It’s part of the Millennium Mathematics Project based at the University of Cambridge. My job there involves writing articles, producing podcasts and videos, and editing other people’s submissions. We cover anything from abstract algebra to astronomy, and theoretical physics to the science of sport.

(…) Once you have an explanation of something in very simple terms, you’ve done some of the hardest part of the work that’s needed to explain it accessibly to others

Starting at Plus was quite a gear change initially. My command of English no longer felt like such an obstacle, but I had no journalistic or writing training. I did a couple of writing courses offered by Cambridge University, but all the really important stuff I learnt on the job from the two brilliant writers and editors then working on Plus, Rachel Thomas and Helen Joyce, and by example from my boss, the amazing John D. Barrow (who sadly died last year).

Ironically, my ignorance also helped me with my writing, I think. I knew almost nothing about most areas of maths, let alone other sciences. This meant doing lots of reading and then explaining things back to myself in baby language — and once you have an explanation of something in very simple terms, you’ve done some of the hardest part of the work that’s needed to explain it accessibly to others.

As a young researcher I’d internalised a fear of asking stupid questions, but as a maths communicator questions are your most important tool

While writing gave me lots of joy, other things were harder to learn. When I started at Plus, I think many mathematicians weren’t as familiar and comfortable with public engagement as they are now. I struggled sometimes to be taken seriously. As a young researcher I’d internalised a fear of asking stupid questions, but as a maths communicator questions are your most important tool. It took me a while to work that out and learn the courage to ask.

Today things are a lot easier in that respect (though I still sometimes spend ages trying to figure something out when I could just go and ask someone). The reason it’s easier is probably that attitudes towards science and maths communication have changed, and that I am older, a tiny bit wiser, and a little more confident.

At the moment we are collaborating with a group of diseases modellers (called JUNIPER) who have been advising the UK government, to bring important concepts and issues about COVID to a general audience

I love my job because it allows me to do what research didn’t: to learn a lot about all sorts of topics but without having to dig too deeply into the technical details. I get to meet amazing people and there are lots of opportunities to branch out and learn more. Rachel and I recently worked as science editors on a Discovery Channel series about the work of Stephen Hawking and privately co-wrote three popular maths books. At the moment we are collaborating with a group of diseases modellers (called JUNIPER) who have been advising the UK government, to bring important concepts and issues about COVID to a general audience. I feel very fortunate to have been given these opportunities.

To someone who’d like to go into science communication as a career, I’d say to get a good grounding in maths before (or while) you’re getting training in writing and communicating. Maths is everywhere in science, and if you can vaguely understand the maths in a piece of science, then you’re already a good way to understanding the rest.

May

2021

Ellese Cotterill

Born in Newcastle, Australia • Studied Advanced Mathematics at the University of New South Wales in Sydney, Australia • Highest Degree PhD in Computational Neuroscience from Cambridge University, UK • Lives in Sydney, Australia • Occupation Data Scientist

From as early as I can remember, I was always interested in maths and numbers. My grandad used to tell the story of me as a young child adding up the numbers on the back of buses on the way to pick up my sister from school. At school, maths was my favourite subject and something that I found came easily to me. When I finished high school, I really didn’t have any clear idea of what I wanted to do as a career, which made picking a university degree difficult. I wanted to do something where I felt like I was positively contributing to society, and a job in a medical field seemed like an obvious choice. For a while I considered medicinal chemistry, but being in a lab was never very appealing to me. In the end I decided to study something I knew I enjoyed, and so I enrolled in an advanced mathematics degree. My parents were quite confused why I didn’t choose a degree with a defined profession such as medicine or law, and questioned me about what kind of career I could have after studying mathematics. I didn’t have a good answer for that, but felt confident that if I did something I enjoyed, the career aspect of things would work itself out later.

(…) My grandmother was suffering from Alzheimer’s disease, so the possibility of making a contribution in that area by studying the brain was very appealing.

In my second year of undergraduate study I discovered the subject of biomathematics, which involves using quantitative methods to study the biological world. I found it really interesting, and ended up doing my honours project in the field, modelling molecular diffusion in cells. When I came to the end of my degree, however, there still wasn’t an obvious career path for mathematics graduates. Careers days were dominated by financial institutions, and I ended up accepting a position as a quantitative analyst at a large investment bank. It only took me a few months to realise this wasn’t the right path for me, and I started looking for other opportunities. I’d enjoyed the research aspect of my honours year, and so thought a PhD in a field like biomathematics could be a good option. There wasn’t much research happening in Australia in this area, but I read a lot coming out of UK universities such as Oxford and Cambridge. Coming from Australia, I’d never imagined that I would be able to get into such prestigious universities, but decided there was no harm in applying. At that time, my grandmother was suffering from Alzheimer’s disease, so the possibility of making a contribution in that area by studying the brain was very appealing. I managed to find a supervisor at Cambridge University working in the field of computational neuroscience, and was lucky enough to be accepted into a Wellcome Trust programme that would fund my PhD in that area.

I greatly enjoyed my time studying in Cambridge, and met a lot of interesting people. One thing I noticed was that although there were many talented female PhD students in the mathematics department, I met almost no female postdoctoral researchers. I believe the impermancy of contracts and often frequent relocation involved in the early stages of an academic career are aspects which turn women off pursuing academics, particularly those who want a family. These were certainly factors that influenced my decision not to continue in academia, and at the end of my PhD I instead looked for opportunities in industry back in Australia.

(…) Choosing to study mathematics has given me fundamental skills in logical reasoning and problem solving which can be applied across many industries and careers.

I spent a year working as a data scientist at a neurotechnology startup in Sydney, but found that the company’s small size meant that it was difficult to produce any meaningful insights with the limited amount of data available. I also realised that I was more interested in working on challenging and meaningful problems from a mathematical perspective, rather than their precise applications. These factors lead me to take a position outside neuroscience, at an aerial imagery company called Nearmap. I’ve been working there for over two years now, helping build models and systems for automatically detecting objects in aerial imagery. I’ve greatly enjoyed my time there, and have been lucky enough to work with a number of talented women within the artificial intelligence team.

If there’s any advice I would give young people choosing what to study, it would be to do what you enjoy and are passionate about, and don’t worry too much about a degree’s application to a career path. My job today isn’t something I would have imagined doing while at university, at which time the field of machine learning as it is today barely even existed. Technology advances so rapidly that it’s impossible to predict what the most exciting and important careers might be in the future. However, choosing to study mathematics has given me fundamental skills in logical reasoning and problem solving which can be applied across many industries and careers.

Apr

2021

Carolin Trouet

Born in Trier, the oldest city of Germany • Birth year 1966 • Studied Business Mathematics at the University of Trier • Highest degree Diploma in Business Mathematics • Lives in Mainz, Germany • Leading teams in Software Development and acting as Chief Agility Master in the Airline IT Industry

In primary school, I struggled with math. My mother put a lot of effort into making me understand the difference between “plus” and “minus”. We were the first kids in Germany familiarized with set theory, working with books but also with these small boxes with plastic shapes of squares, circles, and triangles in different colors. My fascination for math started with geometry, with divisibility rules that our primary school teacher encouraged us to identify by ourselves and with the first mathematical proofs. When I was at grammar school, our teacher in mathematics told my mother: “She will never study mathematics, she is too lazy.” He was right about the laziness. My nickname is sloth, as I love lying in my hammock reading books. But I was fascinated by the ability of mathematicians to transform one problem into an equivalent one we can (easily) solve. The University in my hometown organized an open day and I attended some lectures. That’s when I decided to study math. It was a lecture about infinity and one on how to describe oscillations. This convinced me finally. When I was at university, our professors told us: “Later in your job most of you will never deal with mathematical problems like at University.”

Contrary to my professors’ prediction, I was one of the rare species among my fellow students who applied what we learnt at University.

My professor in numerical mathematics gave me the opportunity to work in a research project on optimization in robotics. Moreover, I received the opportunity to present the project at the industry exhibition in Hanover. He gave me trust, which created self-confidence I never had before. He changed my life. At this exhibition, I met my later husband. As he was living in the Rhine-Main-Region, I skipped my plan to obtain a PhD at my University. Instead, I searched for a job. This is how I started working in a very fascinating industry, the airline IT, as a software engineer in the area of flight optimization. Dijkstra for many years was and still is the algorithm of choice for solving shortest paths problems. At least it is a good basis. It is no longer sufficient due to many influencing factors such as regulations of air traffic flow. Cost optimality means reduction of fuel consumption, but also of overflight costs that are very hard to model. Contrary to my professors’ prediction, I was one of the rare species among my fellow students who applied what we learnt at University. Of course, not all problems in our industry are of this complex nature. However, developing algorithms and implementing software was complicated enough to keep me enthralled. So finally, both were wrong, my math teacher who said I would never study mathematics and the professors. Or did I want to prove them wrong?

It is a welcome change in a captivating profession of forming high performing teams, of dealing with trust-building and the soft facts of human interaction.

After 7 years, I decided to do something completely different. With my knowledge about software production, I joined a small team, the staff in the strategy department of our company. I gained insight into many different departments, sales, production, evaluation of acquisitions and business plans. Finally, I realized software production fascinates me most. So I returned, working in the role of a project manager for a completely new product development. Growing more and more into the leadership role, I was responsible for forming teams to build and operate many of our software products, applications managing the schedule preparation and operation of our airline customers worldwide. After 20 years, I returned to my roots, flight optimization. Developing algorithms for trajectory optimization is not my occupation any longer. Today, I am acting as a sponsor for our projects with the Zuse Institute in Berlin. It is a welcome change in a captivating profession of forming high performing teams, of dealing with trust-building and the soft facts of human interaction. I feel privileged, working in an international environment with diverse teams. Enhancing my knowledge by newest research in neuroscience and systems thinking is combining my private interest and profession.

The combination of rationality and empathy is not only possible; it is the theme of my story.

My favorite shape is the circle. Or is it more an upward spiral? Trust creates self-confidence. This is what I learnt in the research project at University and from my professor and my husband, who encouraged me very much in my professional development. Feedback and reflection create learning and improvement. The most amazing teams I know learnt from their mistakes and never stopped deriving actions to improve. Fearlessness creates the willingness to take responsibility. This describes very well the environment in which I could and still will grow from one role to the next. I had and still have colleagues and superiors I can talk to very openly, speaking my mind. I am not “punished” but supported in case things go wrong. As a mathematician, I have shown my ability to solve complex problems, as a leader I need to support teams to grow in a changing world. I love the following quote from Virginia Satir very much: “We get together on the basis of our similarities; we grow on the basis of our differences”. The combination of rationality and empathy is not only possible; it is the theme of my story.

Apr

2021

Jamie Prezioso

Born in Warren, Ohio, United State • Birth year 1989 • Studied Applied Mathematics at Case Western Reserve University, Cleveland, Ohio, United States • Lives in Washington, D.C. United States • currently a Research Scientist

Growing up, I genuinely enjoyed math from an early age. I have fond memories of solving equations and homemade arithmetic flash cards with my grandfather. He consistently and lovingly encouraged me to pursue math. And so, I did.

I had an inclination that studying mathematics would open an array of opportunities, however, I had no tangible examples of this. Nevertheless, I was drawn to pursue math.

I happily studied and excelled in mathematics throughout middle and high school. When choosing a major in college, I did not even consider math. Having never seen or learned about modern-day mathematicians in school or media, I was unaware of this entire profession. Since I was also interested in medicine, I considered studying biology. I knew of clear academic and career paths in the medical field. Ultimately, my first year in college I was undecided. I had an inclination that studying mathematics would open an array of opportunities, however, I had no tangible examples of this. Nevertheless, I was drawn to pursue math. And so, I did.

I began to discover the ways you could use mathematics to solve problems I found interesting and important, like quantifying the effects of climate change or modeling predator-prey dynamics in fragile ecosystems. I graduated from Walsh University with a Bachelor’s of Science in Mathematics. When applying for graduate programs, I had every intention of obtaining a Master’s degree in a few years and leaving the program for industry. The thought of being in school for nearly all of my twenties seemed unbearable, if not impossible. I did not want to wait for my professional career, and in some sense my “adult” personal life, to begin. Still, I was excited to pursue math. And so, I did.

Through coursework and research, I found I was truly passionate about math. I developed strong quantitative modeling and coding skills. I even got to study areas of biology and medicine.

In the Fall of 2012, I began graduate school at Case Western Reserve University. I studied applied mathematics, taught Calculus to bright undergraduates and conducted research in mathematics and computational neuroscience. It was in graduate school where I grew both personally and professionally. I had many wonderful experiences with brilliant mathematicians from all over the world, many of whom I am still close with today. Through coursework and research, I found I was truly passionate about math. I developed strong quantitative modeling and coding skills. I even got to study areas of biology and medicine. I gained confidence in myself and a deeper understanding of mathematics. And so, I obtained a PhD in Applied Mathematics.

I use my background in mathematics to research machine learning (ML) and artificial intelligence (AI) models […]

Now, I am an Applied Mathematician. I am a Research Scientist at a consulting firm in the Washington, D.C. area. I use my background in mathematics to research machine learning (ML) and artificial intelligence (AI) models, focusing on interpretability and explainability. While AI/ML models have proven extremely useful on a variety of tasks, their inherent black-box nature and lack of interpretability limits their use in critical applications, like medicine or autonomous driving. Specifically, I research and develop neural networks, mathematical models which are typically highly over-parameterized but have exhibited superior performance on high dimensional data (e.g. images), trying to better understand how these models make predictions, assess their confidence and incorporate prior expert knowledge.

I feel very fortunate to have a career which aligns with my field of study and allows me to work on problems I am passionate and excited about. I hope that my story, and the stories of the other women here, highlight the vast number of exciting opportunities and careers in mathematics, the careers that I was unaware of for so long.

Apr

2021

Dr Beate Ehrhardt

Born in Walsrode, Germany • Birth year 1987 • Studied Mathematics in Bremen, Germany • Highest Degree PhD in Mathematical Statistics • Lives in Bath, UK • Occupation Mathematical Innovation Research Associate at Institute for Mathematical Innovation, University of Bath

I am a 33-year-old applied mathematician and data analysis expert with a PhD in Mathematical Statistics from University College London. I hold a permanent, research-only position at the Institute for Mathematical Innovation (IMI) at the University of Bath. Before joining the IMI, I worked as a Senior Research Statistician at the global pharmaceutical company AstraZeneca. I have a 2-year-old daughter and am expecting my second child any day.

Growing up with two sisters and a brother, my father never told us there was a difference between boys and girls. Instead, he instilled in us an understanding that we can achieve what we want with hard work. As a result, whenever people tell me I cannot do something I take it as a challenge rather than a dead-end.

I love mathematics. I love learning. I love people. And I love science. But most of all I love when all of these four things come together.

Ask for advice but know how to interpret it

Any kind of advice you receive from others says much more about them than about you. When I was deciding what to study after my A-levels, a teacher for advanced maths advised against “studying mathematics because it is too hard”. He was wrong. I loved every second of my undergraduate programme in mathematics. All of a sudden I was surrounded by like-minded people and could solve riddles day in and day out. Studying mathematics was the best choice for me. It was intense – and yes – it was hard work, but it was so rewarding. I learned to describe the world in equations, see the world in trends, identify patterns, and extract information from all the noise. I found a way to explain the world and found out I was really good at it! Looking back on it now, I understand that my teacher was not judging whether I would be good enough to study mathematics but rather was projecting his own experiences and difficulties studying maths. That is why I would suggest: Ask for advice but know how to interpret it.

I particularly enjoyed the statistics part of my undergraduate degree but wanted to understand further the maths behind it. So, I decided to pursue a PhD in mathematical statistics. Having been abroad to Cardiff, UK for an ERASMUS exchange during my undergraduate, I knew I wanted to be in an international environment surrounded by people from many different backgrounds and cultures for my PhD. When I heard about a PhD position at University College London on the mathematics of networks I was immediately intrigued. Before signing up, I met twice with my future supervisor, which was an incredibly good opportunity to get to know him and his team a little bit. I believe the PhD experience is strongly influenced by the research group you are joining and thus, I would very much recommend trying to find out about them as much as you can. In contrary to the common stereotype that a PhD in mathematics is lonely, I experienced quite the opposite. I joined a small research group of brilliant colleagues – some of whom I still call up nowadays to discuss research ideas, and I also was part of a cohort of PhD students that formed a support network for each other. There was always someone to discuss Maths with, or to join me for a pint when a break was needed.

(…) the very best you can do for you and your career is to discover what gets you out of bed in the morning with a smile

During my PhD, I discovered my talent for proving theorems, and there were multiple opportunities to do a Postdoc on related topics. However, being good at something does not always mean it is what you enjoy doing most. At UCL, I was fortunate to be exposed to many different types of research, which enabled me to understand that what really fascinates me are the insights one can draw from data and the corresponding impact rather than the actual tools used. So, after four years of carefully building a network and investing time and effort to build a strong foundation for a research career, I made (what felt like) a radical decision to leave academia and to join the research-end of industry where I can apply my knowledge to add insights to science with an immediate impact to the real world. Many colleagues and friends were shocked by my move including the research group I was part of, which made the decision even harder.

Now, five years after finishing my PhD, I know it was undoubtedly the right move for me for two main reasons. First, the line between industry and academia is not as rigid as I thought. The move from a research-in-industry position back to academia is increasingly common, and the work I do now at the Institute for Mathematical Innovation is from a mathematical point-of-view very similar to my work at the pharmaceutical company. Second, and most importantly, the move enabled me to experience research in a very applied setting. Most of the work I have done post-PhD has involved engaging with multi-disciplinary teams working together towards an overarching goal. Each new project comes with its own data analytical challenges while at the same time allowing me to learn about research in a variety of disciplines. Whether it is tiny scissors that allow us to edit DNA (called Crispr Cas9) or contributing to our knowledge about the growth of black holes, the work is always fascinating. Everybody’s motivations are different and the very best you can do for you and your career is to discover what gets you out of bed in the morning with a smile.

Mar

2021

Patricia Egger

Born in Zurich, Switzerland • Birth year 1990• Studied Mathematics at EPFL in Lausanne, Switzerland • Highest degree Master’s in Applied Mathematics • Lives in Lausanne, Switzerland • Occupation Information Security Officer

I would love to say that my decision to study math was well thought out, but the truth is it really wasn’t.

At the end of high school, I knew I wanted to study a scientific subject at university and set my sight on chemistry. I think I was attracted to the experiments with cool colors, incredibly fast temperature changes and the idea of learning how to create little explosions. However, about 2 months before the first day of university, I changed my mind and signed up to the math department instead. I’m still not sure I know why I changed my mind; I had done well in high school but had no long-term plan or idea of what kind of math I wanted to do or even what type of job I might be interested in. In any case, it seemed like a good idea at the time.

My first year in math was a wake-up call; high school did not prepare me for mathematical reasoning. But I kept studying hard and after the first year and many hours spent in the library, it clicked. I felt like there was no class I couldn’t ace (with enough effort, of course). From there on, it was relatively smooth sailing until I graduated with my Master’s degree a few years later.

I looked for inspiration in the news; who doesn’t want to be working on a topic that gets regular media coverage?

It was at that point that my lack of long-term thinking caught up with me. In fact, as much as I enjoyed studying math, I couldn’t seem to find a math-related job that tickled my fancy. Instead of taking a job that I didn’t want, I decided to look for an entirely different field and career path where my math skills could be used indirectly. I looked for inspiration in the news; who doesn’t want to be working on a topic that gets regular media coverage? Similarly to today, cybersecurity, particularly cyber incidents, came up often. That’s when I remembered a basic cryptography class I had taken in middle school and that I thoroughly enjoyed. Because cryptography is essentially math, it seemed like it would be my opportunity to shift into cybersecurity. So I went back to university for a semester to take all the security-related courses I could.

Fast forward a few years and I now work as an information security officer. In my current role, my main goal is to manage cybersecurity risks: understand what might go wrong and how, and ensure we are allocating appropriate resources accordingly. As these risks are present throughout any organization, I interact with many different people on a regular basis, be they developers, lawyers or Top Management.

In fact, I have been very fortunate to meet amazing women and men along the way from who I’ve learned a lot, but I most definitely would not be where I am now if I had tried to base my career on theirs.

Although I don’t use much of my math background in my daily work today, it allowed me to get to where I am today and I don’t regret any of it. On the contrary, I believe my studies gave me some great transferable skills and the confidence to navigate all of the changes and decisions I made along the way.

Although many people influenced and supported me throughout this process, I’m glad I never took anyone’s opinion more seriously than I did my own. In fact, I have been very fortunate to meet amazing women and men along the way from whom I’ve learned a lot, but I most definitely would not be where I am now if I had tried to base my career on theirs.

Jan

2021

Lena Frerking

Born in Münster, Germany • Birth year 1988 • Studied Mathematics in Münster, Germany • Highest Degree PhD in Mathematics • Lives in Hamburg, Germany • Occupation Research Scientist in Medical Imaging

The decision of what to study was not clear to me for a long time. I always liked math, but I could not really imagine what a job as a mathematician could look like. Only after discussing with family and friends at the end of my high school time, but especially with my godfather who very convincingly told of his positive experiences of working with mathematicians and of the usefulness of their skills, I discovered the diversity of applications. Being a person who had always been struggling a bit with making decisions, I immediately liked the idea of not limiting my future job perspectives in industry by the choice of the subject. I probably made my final decision during one of the annual university events where high school students can attend different university lectures for one day. Since I was quite undecided, I prepared a schedule and planned to attend lectures in different departments, amongst others in the medical and pharmaceutical department. I had seen some math lectures before and I liked them a lot, so I wanted to explore other options and focus on subjects other than mathematics to try and see if I would like those even more. So, I decided to attend a pharmaceutical lecture, but I knew immediately that this was not going to be my profession. I left 10 minutes after the lecture started and just went over to the math department again to yet attend another lecture. As soon as it started, I realized that the only reason I went there was to treat myself at the end of the day, because I knew I would enjoy it. That insight finally led me to the conclusion that I did not need to continue searching for anything else. I had already fallen in love with mathematics, especially the logic and the fact that everything makes sense if one just follows every single step in calculations or proofs accurately.

In the end, it did [work out], and I am more than happy that I took the risk to fail.

In the beginning of my math studies, I was surprised about the speed of the actual lectures and how different they were from the classes taught in school. I never regretted my decision, but the first two or three semesters were not easy for me to master. However, things became easier once I was able to specialize further in my studies. Even though I always thought I wanted to stay away from numerical mathematics, I eventually ended up putting the entire focus on applied mathematics and I also specialized in this field during my Master’s. Despite my previous hesitation, I quickly realized how much I liked the lectures and that they suited me more than the purely theoretical ones. The question about whether to do a PhD or not was a tough one again. I was doubting myself, but I already knew deep down that I had to give it a try. Otherwise, I would have always regretted not trying and wondered whether it would have worked out. In the end, it did, and I am more than happy that I took the risk to fail.

(…) I am happy that I still need many of the concepts and techniques that I learned at university.

After finishing my PhD, I left academia and I am now working in industry. I feel lucky that I still work in the same field I researched when I was at the university with similar applications in medicine. Therefore, the transition from academia to industry was quite smooth. Even though mathematicians are often in high demand on the job market for their way of thinking, but not necessarily for the direct knowledge obtained in math lectures, I am happy that I still need many of the concepts and techniques that I learned at university. I work in medical image computing and contribute to different aspects of enhancing CT and MRI acquisitions. Hence, I still apply some learned algorithms and I can also still be creative in the way of optimizing and adapting them to be suitable for specific applications.

Jan

2021

Dr Camilla Schelpe

Born in UK • Studied Theoretical Physics at Cambridge University, UK • Highest Degree PhD in Theoretical Physics • Lives in Cambridge, UK • Current Occuptation: Quantitative Researcher at GAM Investments

I think I was very fortunate that as I grew up, what I was interested in and what I was good at aligned, so that even well before applying to university, I knew I wanted to study astrophysics and general relativity. Really, I think the seed was planted when I was about seven years old and my parents got me Patrick Moore’s “The Starry Sky” – an introductory book for budding astronomers. By a stroke of luck, my family moved to South Africa a few years later, and with the beautiful southern skies to gaze up at, my vague interest in astronomy became a cherished hobby. In retrospect, my parents and sister were amazingly supportive, but I took it completely for granted at the time. I remember family observing holidays in the Karoo (a semi-desert outside Cape Town), visiting the SAAO in Sutherland on their public open days, and camping out until 4am to observe Comet Hale-Bopp in ‘95.

I had a one-track mind about studying physics at university, and I specialised as quickly as I could into astrophysics and cosmology.

My early interest in observational astronomy developed into a much stronger theoretical interest as I got older and discovered that I found maths and physics intuitive and easy compared to other subjects at school. I had a one-track mind about studying physics at university, and I specialised as quickly as I could into astrophysics and cosmology. My PhD was focussed on a particular model to explain dark energy within modified theories of gravity, and I spent a happy four years exploring the possible astrophysical signatures that could lead to detection and proof, or disproof, of the model.

However, during my PhD I came to realise the difference between pure academic learning and a career in academic research. I loved learning about cosmology, but when it came to research, I found the techniques for making progress weren’t very field specific – I was chipping away at the corners of the unknown without much day-to-day exposure to the bigger picture. Those techniques could equally well be applied to other applications with just as much satisfaction.

I made the leap at the end of my PhD to join a small hedge-fund in Cambridge.

Funding is a constant challenge in the pursuit of any academic career and stability comes late in life, if at all. Shining as an alternative was a career in quantitative finance – either in a bank (to price exotic derivatives quickly and reliably) or in a hedge fund (to find patterns in data and design computer algorithms to predict the markets and manage risk). The advantages: no prior finance knowledge required, plenty of maths to keep you busy, a PhD is valued, and you are surrounded by a team of like-minded colleagues working towards a common goal. In my spare time, I started playing around with quant trading strategies, using Matlab and end of day close data from the stocks trading on the DAX, and really enjoyed the challenge, although in retrospect I look back in horror at how naïve I was and almost certainly overfitted the data. I made the leap at the end of my PhD to join a small hedge-fund in Cambridge.

They instilled in me a sense that anything was possible if you were interested and worked hard.

I have been extremely lucky to have two amazing, strong role models in my life: my mum and older sister, so if anything, I have a subconscious bias to see women as more successful! They instilled in me a sense that anything was possible if you were interested and worked hard. Also, I was home-educated from the age of nine, and so sheltered from much of the peer-pressure and judgement that a lot of teenagers experience. I only really woke-up to the existence of a gender imbalance in the sciences quite late in life. Both as a student and at work, I have (and I realise I may have been lucky in this respect) always felt I was being treated as an individual, and not categorised as a woman, whether for positive or negative discrimination. There is such a diverse range of personalities, both male and female, that seem much more important than any simple gender divide. I hope we can move towards recognising that as a society.

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