Careers in Quantitative Finance 2026/27
We will be hosting a number of presentations from prestigious companies in industry. This should give you an insight into working in industry and what careers are available to you. Details of this year's speakers will be updated when they are confirmed, and previous speakers can be found by clicking on the links in the menu.
Unless otherwise stated, the Careers in Quantitative Finance Seminar starts at 15:30 in L3.
Wednesday 14th October 2026 - Barclays
- John Taylor
- Gaurav Mittal
- Sylvestre Burgos
- Ted Xiong
- Vicky Chen
- Varin Adhiphandhuamphai
- Ryan Liu
- Ismael Baroudi
- Richard Mathers
Wednesday 21st October 2026 - Deutsche Bank
Hear from business representatives at Deutsche Bank who will share insights into their day to day, the Quant structure and give advice on pursuing a career in Quants.
- Aisha Xu
- Maxwell Fulford
Wednesday 28th October 2026 - ExxonMobil
Quantitative Finance in Energy Trading: Research Challenges and Internship Opportunities at ExxonMobil
What does quantitative finance look like outside traditional banking and asset management? Energy trading offers a rich set of problems at the intersection of mathematics, computing, economics, and real-world physical systems. In this presentation, members of the ExxonMobil's Quantitative Analytics organization will provide an overview of how quantitative researchers support global trading activities across gas, power, LNG and other energy markets. They will discuss the structure of the team, the trading businesses they partner with, and the diverse range of problems they tackle, spanning derivative pricing, risk management, optimization and systematic trading. They will then present a number of internship projects that reflect current research challenges faced by the teams. These include developing stochastic models for gas and power markets, constructing high-resolution forward curves from market quotes and fundamental data, exploring advanced volatility models for LNG optionality, designing quantamental trading strategies that combine machine learning with supply-and-demand signals, and building high-frequency simulation frameworks for strategy evaluation and execution analysis. The talk is aimed at students with interests in mathematical finance, statistics, machine learning, optimization and scientific computing. Beyond presenting individual projects, the ExxonMobil quant team hopes to provide a glimpse into how rigorous quantitative methods can be applied to complex real-world markets, and to inspire students interested in pursuing internships and careers in quantitative research at ExxonMobil.
Wednesday 4th November 2026 - Rothesay
Quantitative Strategists at Rothesay
Rothesay is the UK’s largest specialist pensions insurer, managing more than £74bn in assets and securing the pensions of over one million policyholders. With a singular focus on pensions insurance, Rothesay combines sophisticated technology, rigorous quantitative analysis and real-time risk management to solve complex, long-term financial challenges. Across the business, teams look for opportunities to do things differently—and better—while maintaining an absolute focus on security, precision and excellent policyholder care.
Members of Rothesay’s Quantitative Strategist (“Strat”) team will offer an inside look at how mathematics, computation and financial theory are applied to important problems across the business. Speakers from the Liabilities and Assets Strat teams will introduce the breadth of the Strat role, share examples of the challenges they tackle and discuss how quantitative ideas move from analysis into real-world decision-making. The session will feature both the Head of Liability Strategists and more recent joiners, who will share their routes into the team and their experiences of Rothesay’s internship and graduate programmes, for which roles are currently open.
Wednesday 11th November 2026 - Jefferies
Wednesday 18th November 2026, 14:30 - Schonfeld
Wednesday 25th November 2026 - Haruko
Wednesday 2nd December 2026 - RBC Capital Markets