Education: PhD Evolutionary Genetics (University of Zurich), MSc. Biology (University of Munich)

Expertise: Data Science

Social media details: https://www.linkedin.com/in/bettinaschirrmeister

Since early 2022, I have been leading an exceptional team of data scientists at MoneySuperMarket. Our biggest ambition helping customers save money through smart product recommendations, personalisation, and optimised pricing investments.

I have received a PhD in Evolutionary Genetics from the University of Zurich in 2012 and worked as a senior researcher at the University of Bristol for several years, reconstructing the early evolution of life applying various mathematical models to simulate genetic change over time.

In 2016, I joined the course s2ds by the company Pivigo to support me in a shift away from academia to professional data science. I started the same year working for Royal Mail, originally as a data scientist and following various successful project deliveries, such as the “Estimated Delivery Window” provided for customers, took over as a head of data science in early 2021. In 2022 I left Royal Mail and started at MoneySuperMarket as a head of data science.

I have recently been a guest at the Customer Insight Leader podcast, where  I spoke about the transition from academia to a commercial setting, the skills that academics bring along to a business and the challenges they are facing: https://open.spotify.com/episode/75NDmQ78uJUpsLvY75rYxN?si=2h-vC-aHSk2I7unwL92SIA

Last year, I have presented our latest MLOps pipeline at MoneySuperMarket, which has just started to run the first data science projects e2e, at the annual meeting of the Operational Research Society OR64. Plenary Talk: Connect with your customer – MLOps in action. https://www.theorsociety.com/events/annual-conference/

Education: MSc Data Science, University of Exeter; BSc Mathematical Sciences, University of Bath

Expertise: Data Science, Project Management

LinkedIn: https://www.linkedin.com/in/laura-holdcroft-1b930066/

My experience at college was pivotal in discovering my passion for mathematics. This was largely due to my brilliant tutor who not only inspired me, but also instilled the confidence to pursue this subject despite my initial doubts in myself. Encouraged by this new-found passion and self-assurance, I applied to study maths at the University of Bath. It was there that I discovered just how varied the world of maths is, and that data analysis and coding could go hand-in-hand with maths.

Following my graduation, I embarked on a career path in data analytics. I enjoyed utilising data to uncover trends and provide valuable insights for businesses to make informed decisions. After gaining some experience in the field of analytics, I realised my desire to expand my knowledge in data science. I enrolled in a part-time Master’s program in Data Science whilst working full-time. As I progressed through the program, I began to undertake more projects which incorporated machine learning, an area that I became really interested in.

At MoneySupermarket Group I have had the opportunity to broaden my expertise with machine learning, while also exploring interesting business problems related to guiding pricing strategies and providing personalised recommendations to customers. Partnering with Women in Data, I am excited about discussing the career opportunities available in the world of data, and I aspire to empower more girls to feel confident in their abilities in STEM subjects

LinkedIn: https://www.linkedin.com/in/charlotte-doherty/

I’ve been working in data industry for over 20 years, having stumbled into it accidentally whilst working for the Bank of England.  I’m of the generation that was first required to pay university fees, and coming from a working-class background this wasn’t something I was able to afford without having years to save up towards it.  Instead, I left school after A levels having no idea what I wanted to do for my career.

At the Bank of England, I had a varied experience working first on foreign exchange and then eventually in the monetary analysis division, working for the Monetary Policy Committee.  One day I was asked if I wanted to work on a side project for the intranet – and that’s when I stumbled into web analytics data.  When I was offered the chance to have university sponsorship to become an economist, I turned it down – I knew I needed to follow my passion into data.

I joined Ford of Europe as a contractor working on vehicle product definition.  At Ford I had a revelation: my data skills are industry agnostic, and I can consider data roles in any industry.

From automotive to recruitment, I joined Totaljobs Group as a web analyst.  I worked for the most amazing woman who supported me as I learned so much about digital businesses, especially digital marketing, and statistical modelling.  The role was a jill-of-all-data-trades.  I was incredibly lucky to be working at Totaljobs when I had my first child, and was supported to return to work with flexibility, compressed hours and working from home.

From recruitment into financial services, I took a role at John Lewis working on their data analysis for credit cards and insurance.  In this role, I was still a jill-of-all-data-trades but for the first time I was working extremely closely with design and editorial teams for online and offline teams.  My two years in John Lewis partnership forever changed my approach to data analysis and engineering and embedded in my a customer-centric approach.

Most recently, I moved from financial services into tech by joining Decision Tech.  I inherited a data infrastructure that was slow, unstable, and unsustainable.  I secured funding and resource to rebuild our infrastructure from the ground up.  My goal to support every person in the business with accurate data was achieved by combining data engineering in Google Cloud Platform, AWS to create a new real-time sales and revenue system, and off-the-shelf tooling (like Google Analytics and Tableau).  I had another child, grew the data team, and trained up every member of our small company to make data-led decisions.  In 2018, Decision Tech joined Moneysupermarket Group, and in 2021 I grabbed the opportunity to become head of data systems to engineer a more sophisticated GCP architecture.  In 2022, I was pleased to form the data solutions team, to unite data engineers with our business intelligence community.  I am delighted to be part of the transformation of Moneysupermarket Group’s culture of data-led decision making in a self-service environment.

I have been extremely lucky in my career and had tremendous support from fantastic people along the way.  I am now very honoured to be involved in Moneysupermarket Group’s Women in Data and Women in Tech initiatives, to support others in their career development.

Expertise: Data science, Machine Learning

Education: MSc Data Science, MSc Psychology, BA Psychology, BFA Musical Theatre 

LinkedIn: https://www.linkedin.com/in/anna-nguyen-0b4712160/

My aspirations and passions have taken me down several different paths, from studying the Arts, to Humanities and finally to Data Science. Growing up I did not even consider Data Science or Computer Sciences as a career option. I thought I wanted to be a Psychologist or a singer. So whilst at NYU I double majored in both, I even went on to get a graduate degree in Psychology at UCL.

During my Masters in Psychology, I was introduced to my first coding class, and it changed my career trajectory entirely. Here was something I had never studied, and yet I found even more interesting than my current field. It seemed very daunting, but after graduating from UCL I made the decision to switch over to Data Science. I quickly enrolled in as many online resources as I could to try and bridge the gap in my education, and reached out to individuals on LinkedIn to see if I could intern to get industry experience. I followed up by joining a Data Science conversion Masters to solidify and prove to myself that I had the ability to understand and keep up academically within this field.

Today, I am a Senior Data Scientist at Money Supermarket Group. A company who is dedicated to helping people save money. In my team I am developing and deploying machine learning models for rankings and predicting consumer behaviour. I hope that I can introduce this field to other women who have never considered this type of STEM career, and make sure they know it is an option.

Education: MSc in Natural Sciences and Management Studies, University of Cambridge

Expertise:  Product Management, Delivery, Marketing Technology, Data

Social media details: LinkedIn

I had absolutely no idea what I wanted to do when I left school. I knew I was very interested in understanding customers and why they behave the way they do, and therefore the Marketing and Insight roles in Diageo and Tesco I did was a great start to my career.

A major turning point came was when I grabbed the opportunity to move into Tesco International, where I collaborated closely with Tech teams to launch grocery delivery in Europe and Asia. I was really unsure about leaving Marketing back then but the experience to work in different countries was massively appealing.

After my first child was born, I quickly realised a more UK-based role would be more practical, so I went onto lead the development of the Tesco Clubcard Rewards website, followed by another Product Management role optimising e-commerce websites and apps at a Transport provider.

It wasn’t until Just Eat when the breadth of my experience in Marketing, Data and Product came together, and I went onto build data platform, drive innovations such as single customer view, and enable global teams make data-driven decisions.

Looking back, my “squiggly” career has certainly been more “jungle gym” than a typical ladder, but I’ve come to recognise the common themes, mainly around my love for learning new things and my superstrength in problem-solving, and my personal values around growth, having fun and adventure.