Careers in Data Science

A series of informal events to connect LSE students with employers

The Careers in Data Science event was one of the best things I’ve been to in my time at LSE

Thomas, postgraduate student

The LSE Data Science Institute’s Careers in Data Science series aims to connect students with people working in data science who have made the transition into industry.

Held twice per term, these events are open to all LSE students with an interest in pursuing a career in data science or related fields. Our series features guests with experience of both the public and private sectors, including early career professionals as well as established leaders. 

The Careers in Data Science series provides opportunities to find out more about pursuing a career in data science in an informal environment. Each presentation is designed to be conversational in tone. Audience questions are encouraged and there is further opportunity to ask questions and network with refreshments after the presentation.

The DSI welcomes interest from businesses and alumni who would like to support future events as sponsors or guest speakers.

Please complete this form if you are interested in supporting these events.

  • Careers in Data Science
    We invite businesses and alumni to support future events as sponsors or guest speakers.
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For more information please contact 

Upcoming Events


Keeping London Moving with Data 
28 February 2024 | 4.00pm to 5.30pm

Event open to LSE Students only | Sign up to attend

TfL is London’s integrated transport authority running the day-to-day operation of the Capital’s public transport network and managing London’s main roads. Millions of journeys are made each day on our transport network, generating millions upon millions of bits of information. Translating this vast amount of data into intelligence to drive improvement is our goal. And do that, we rely on data to inform our operations and planning and customer services.

We’ll talk about life in the data world at TfL. Jemima will talk about her experience as a Data Science Graduate in our inaugural programme. Lauren will talk about how she’s leading TfL’s data strategy, and how all the components of data careers (data scientists, data developers, data product managers, and data users) can come together to deliver on our data vision: To empower our people to make better decisions with data.


Lauren Sager Weinstein

Lauren Sager Weinstein

Lauren Sager Weinstein, Chief Data Officer, at Transport for London (TfL), leads TfL in using our vast amounts of system data to transform how TfL plans and operates transport in London. Lauren created TfL’s Data and Analytics department, building a team of data scientists, data software developers, and analytics translators who provide data tools for TfL to understand customer travel behavior, and analytic tools to operate and plan London’s vast transport network. Her team’s analysis has been instrumental during the challenges during Coronavirus, providing TfL, London city officials, UK Government, and the public with information about how travel changed during the Pandemic.

Lauren joined TfL in 2002 and she’s held a variety of roles, working on many projects, including the launch of the contactless payment system across London’s transport network. Originally from Washington, DC, USA, she has degrees from Princeton University and from the Harvard Kennedy School of Government, who awarded Lauren the 2019 Alumni Award for Digital Innovation. Lauren was named the 2017 UK Chief Data Officer of the year by the CDO Club, and was honoured to be included in The Female Lead’s 20 role models in Data & Technology 2017. She’s also made an appearance on the DataIQ100 List for several years. 

Jemima Clifford

Jemima Clifford  

Jemima Clifford is a Graduate Data Scientist at Transport for London (TfL) currently in her second year of TfL’s Data Science Graduate Scheme. Jemima studied Civil Engineering at the University of Bristol and worked as a structural engineer for two years in London before joining TfL’s graduate scheme in 2021. Through the graduate scheme Jemima has worked in a variety of teams within TfL including Data & Analytics, Asset Reliability, and Environment & Sustainability Engineering. Jemima’s work as a Data Scientist predominately involves using Python and R to apply analytical techniques and machine learning algorithms to gain insights from datasets and facilitate data-led decisions within TfL. 

Women in tech SU

Event Partner: Women in Tech Student Union

For this event we are partnering with the LSE Women in Tech Student Union. Founded in March 2022, LSESU Women in Tech has been developed to empower women empower women to enter the world of technology.

Find out more about LSEU Women in Tech

Past Events

In Data Science, Context is Key but Passion is even Better!
28 November 2023

In Data Science, Context is Key but Passion is even Better!
28 November 2023, 16:00 - 17:30

From gaming to e-commerce to customer engagement, data science continues to make a positive impact on countless industries. Knowledge of subject matter is necessary however a passion for the area is a great place to start (and of course if you have both, that’s the best)! Getting to work with subject matter experts and business stakeholders is an integral part of the data science process therefore working in a specific area gives you the opportunity to learn more about it and potentially become an expert yourself.

In this presentation, Lareina will share how she has leveraged her research and data science skills to work in areas of passion and to drive impact with unbridled enthusiasm. She will give an overview of her background, indirect route into data science, and how context and passion has motivated her and propelled her career forward.


Lareina Milambiling

Lareina Milambiling, Senior Data Scientist 
The LEGO Group   

Lareina began her career in academia, researching theoretical Austronesian morphosyntax while completing her Master of Arts in Linguistics. She then shifted gears, completing a Master of Science in Computer Science, with thesis research focus on NLP and AI within the context of computer-based games, while also completing an internship at Big Blue Bubble Inc. 

After moving to the UK, Lareina applied her research experience to the fashion e-commerce industry, working in data for 2 years at Lyst followed by 4.5 years at Amazon Fashion. Lareina now works as a Senior Data Scientist in the Incubation team at The LEGO Group, experimenting with innovative approaches to brand and customer engagement optimisation. She is also a Data Science Co-Chair for the Grace Hopper Celebration, hosted annually by, mentoring, supporting and shaping data science training offerings. 


Data Science as a Career and a Side Hustle
24 October 2023

Data science is a career which can pay tremendously well, but it also gives you the skills to be an entrepreneur. In this presentation Ben will explore how he has taken his experience as a Lead Data Scientist at John Lewis and Waitrose and applied it to launching a side hustle. 

Ben will give an overview of his background, his role at John Lewis, what it has been like building a startup. He will discuss how the types of data science projects taken for granted at multi-billion pound companies are only just starting to trickle out to the wider economy, and why this presents an amazing opportunity for anyone with programming skills and an interest in building. 


Ben Marshall

Ben Marshall, Lead Data Scientist 
John Lewis & Partners  

Ben began his career working in quantitative economics for an AI focused hedge fund. He then moved to work at one of the world's largest sovereign wealth funds (GIC) as an Associate VP and lead data scientist in the European Private Markets division. Following the birth of his son, Ben moved to the retail sector, where he has led data science in operations for John Lewis and Waitrose. He also runs a small SAAS company providing ML derived pricing solutions to e-commerce businesses, Ben has Master's degrees from the LSE and the University of Bristol. 


Data Science - the new silver bullet in retail?
16 March 2023

How is data science is helping retail business to create new revenue channels, improve efficiency, reduce working capital, become cybersecure, increase customer loyalty and accelerate sustainability? 

Machine vision, structures/ unstructured data and hyper automation using ML, supervised/ unsupervised learning models and hyper personalisation are transforming retail. In this interactive lecture, Sunil Ramakrishnan will discuss real life examples of how data science has become a critical strategy at retailers like Amazon, Alibaba, Netflix, Disney, Nestle, Co-op, ZARA, OpenSea etc. Sunil will discuss the failures and successes in this path, learnings and the value being realised.   

Sunil argues that data science is now the new silver bullet for companies in their defensive strategies where an incumbent is fighting new competition to lead as well in new offensive strategies where a new disrupter is creating a new blue ocean and taking away customers from lazy incumbents.  


Sunil Ramakrishnan

Sunil Ramakrishnan  
Sunil is a Data Science leader and Vice President for Consulting at CGI and a sought-after inspirational speaker at numerous AI conferences across UK & Europe.   

Before joining CGI, he was Chief Revenue Officer & Board member at QiO Technologies (a data science company), Head of AI & IIoT at IBM and Analytics leader at KPMG.  

He has 25 years of experience in consulting with 10+ in using big data, statistics and data science to help retail, banking, energy and manufacturing businesses improve efficiency, reduce working capital, become cybersecure, increase customer loyalty and accelerate sustainability. Experience includes machine vision, structures/ unstructured data and hyper automation using ML, supervised/ unsupervised learning models and hyper personalisation.  

Sunil is an IBM Data Science practitioner, MBA from Imperial College London and has an Honorary degree in Chemical Engineering.  

Connect with him on LinkedIn and Twitter.   

From Tokyo 2021 to the future of AI: my journey as a data scientist
16 February 2023

How does your disciplinary background impact where your career ends up? The answer is - it is up to you!

As a computer scientist with a humanities background, Priyanka Suresh has negotiated the data and tech sector in a range of interesting roles, including five years as a Data Scientist at Google. This gives her experience in a wide range of applied topics within different backgrounds. 

At this event, Priyanka will offer students invaluable insights on the day to day applications of data science gained from her involvement in data projects including the urban planning of travellers for the Tokyo 2021 Olympics. Priyanka will also offer thoughts on broader real world applications of AI and its impact in areas such as climate change.


Priyanka Suresh

Priyanka Suresh
Applied Business Analyst, Deepmind

Priyanka Suresh is a data scientist with 8+ years of experience in academia (Harvard University, Max Planck Institute) and the industry (Deepmind, Google, Softbank). With a dual masters in Computer Science and Humanities, Priyanka uses data as a powerful tool to tell impact-driven stories. Having worked across 7 industries and 5 countries, Priyanka is passionate about socio-cultural implications of data and was part of the advisory board for the Tokyo 2021 Olympics. Priyanka currently works in Strategy & Operations at Deepmind, finding applications of AI research in the real world; and continues to be involved in digital art restoration of South Indian art and Classical Latin texts. 

Moving from talk to practicalities - fairness in machine learning
10 November 2022

Principles for the development of fair machine learning systems are now widespread, however what a development team actually has to do to get things moving is often still unclear. Former students consistently note that becoming aware of this was key to becoming employable. 

This session will dive into some of the practical considerations surrounding the application of fairness, and how society should build trust and understanding of machine learning and other AI elements. The event will provide attendees more understanding of what companies might do to move the needle on this topic.

In an open and informal atmosphere, with refreshments provided, LSE students will become aware of why the practical application of fairness is a key component in moving the conversation forward in how we can use trustworthy AI to reduce risk. This will directly benefit them as they map future careers.

Key takeaways:

  • Why is a fairness framework important?
  • What are the headwinds that a development team faces in the application of fairness?
  • What approaches are available for structuring a fairness solution?
  • How can you approach identifying harms and groups?


Luke Vilian (1)

Luke Vilain
Data Ethics Senior Manager at Lloyds Banking Group

Luke leads a team who design detailed processes and build reusable tooling to support use case teams in addressing fairness and explainability requirements, in a financial services context. Prior to this Luke built development methodologies to support the creation of data science products.

Luke's background is not data science however - he spent 12 years in Accenture as a governance and methodology specialist, working with large programmes to design how they would mobilise and scale to deliver across several dozens or hundreds of projects. 


Data science for management consultancy
20 October 2022

Data science management consulting is a fast-growing sector - but also one that is commonly misunderstood. What is a data science consultant and how do you become one? How is data science being used to help drive businesses innovate and grow?

Our speakers include an experienced professional an a recent LSE graduate. They will offer different, complimentary perspectives on these topics and will be able to provide invaluable insights for current LSE students as they plan a career in this and related sectors. 

These events are held in a relaxed atmosphere with refreshments provided to encourage conversations and opportunities for networking. The chance to ask questions and gain advantageous insight makes this event unmissable for any LSE student interested in pursuing a career in data science.

“It was great to be able to connect with other students and help them with their doubts about transitioning from university to industry. Especially because many of their questions are the same ones we had a few years ago when we were in the same situation.”
Marta and Priyal, Ekimetrics


Mads Frank

Mads Frank
Manager - Behavioural And Data Science for Talent & Organization at Accenture

Mads is an experienced professional who leads on behavioural and data science at a global leading technology company. Mads will outline how the role of behavioural analytics and natural language processing is changing in the post-pandemic, virtual-first work environment. 

Priyal Haria

Priyal Haria
Junior Consultant at Ekimetrics

LSE alumna Priyal will share her experience of transitioning from LSE to industry and the skills required to do so.

Marta Bárcena Rodríguez

Marta Bárcena Rodríguez
Junior Consultant at Ekimetrics

Marta will present with Priyal on a recent project they have been working on with Ekimetrics.


How my degree helps me to work as a data scientist
26 May 2022

As the increasing use of data transforms many industries, one of the main challenges businesses now face is addressing the significant skills gap that exists in the field of data science. At the same time, students struggle to know which skills they should prioritise and develop in order to be competitive as they take their first career steps.

This Careers in Data Science event will explore how the skills and experience from data science degrees translate into industry roles and which skills are the most useful to have at entry-level.

Our guest is a recent LSE graduate working as a Data Scientist at the Greater London Authority who will share insights that would have been helpful during her studies. Our guest will also share experiences of applying for entry-level roles and thoughts on which skills from her degree have been key for entering a data science role as a graduate.

The opportunity to gain such advantageous insight makes this makes the event unmissable for any LSE student interested in pursuing a career in data science.

These in-person events are held in a relaxed atmosphere with refreshments provided. Students are encouraged to make use of this invaluable networking opportunity and continue conversations after the session.  



Tabtim Duenger

Tabtim is a Data Scientist (and alumna of MSc Applied Social Data Science) working at the Greater London Authority. Her work focuses on analysing datasets to inform the development of policy and service delivery through the GLA and stakeholders.

She is currently on the Data Science programme with the ONS working to develop an algorithm predicting high streets at risk in London.

How organisations turn data into decisions 
31 March 2022

The use of data is increasingly key for organisations of all types. Core business processes and decisions are impacted by combining insights from data with engineering solutions.

Guests from QuantCo will share their experiences of leveraging data science, engineering and economics in a way that helps organisations to make decisions.

By relaying real-world experiences at this Careers in Data Science event, our guests will provide invaluable advice and insights to students looking to transition into industry. 

QuantCo's current team members have backgrounds in computer science, mathematics, economics, statistics, and physics. 


Martin Lukac

Martin Lukac

Martin is a Research Data Scientist at QuantCo, where his work focuses on building and improving machine learning systems for fraud detection. Previously, he has been an LSE Fellow in Computational Social Science in the Department of Methodology at the London School of Economics and Political Science and an Associate at the Institute for New Economic Thinking at the University of Oxford. Martin finished his PhD at the Centre for Sociological Research at KU Leuven in Belgium. Get in touch with Martin here.

Peter Schmidt

Peter Schmidt

After growing up in Germany, Peter studied economics there, as well as in Spain and in the United States. He then worked in the Statistics Department of the European Central Bank, before moving to Bocconi University in Milan for a PhD in economics. Peter specialised in Empirical Industrial Organisation, studying the effects of new technologies on incumbent industries, as well as the economics of multi-sided platforms. He then joined QuantCo immediately after completing his PhD in 2019 and has since worked on projects in insurance pricing, process automatisation and fraud detection. Get in touch with Peter here.

How to find your first data science role 
24 February 2022

Many industries are being transformed by advances in data science, but these advances have outpaced skills development and traditional evolution of career pathways. Many graduates face the question: How do I find an entry-level position? 

The inaugural event in the Careers in Data Science series will help students to plan their careers in data science or related fields by providing advice and insights from those that have made the transition into industry. 

Our first guests will be a recent LSE graduate working in the private sector and an experienced leader in the public sector. Their different perspectives will provide invaluable insights for students as they share strategies, resources and advice on how to find entry-level positions.  

These in-person events will be held in a relaxed atmosphere with refreshments provided. Students are encouraged to make use of this invaluable networking opportunity and continue conversations after the session. 


Bio pic

David Dorrell
Competition and Markets Authority

David is an experienced data leader and multi-disciplinary data scientist who has built and led many data functions including data science, data engineering and eDiscovery teams.

David’s experience includes architecting and building data platforms in the cloud (AWS, Azure) as well as delivering data-led projects that use machine learning to deliver new insight and make a real operational impact. David has also delivered presentations at No. 10 Downing Street and at a World Bank Conference. 


Anton Boichenko

Anton is a Product Developer (and alumnus of MSc Applied Social Data Science) who is extremely well placed to offer advice to current students on how to use the skills developed during their time at LSE to navigate the job market.

Anton was recently nominated for an award recognising Outstanding Contribution to Digital Skills at London Tech Week and contributes to LSE Digital Skills Lab courses as a Data Science Tools Trainer, leading sessions on Python, R and SPSS.