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Machine Learning Research Internship

Computer Science/Software/Robotics/Data Science/Maths.

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G-Research is Europe’s leading quantitative finance research firm. We hire the brightest minds in the world to tackle some of the biggest questions in finance. We pair this expertise with machine learning, big data, and some of the most advanced technology available to predict movements in financial markets.

The role

Engineering The Next Generation: G-Research in partnership with the IET & ITN Productions

Engineering The Next Generation

  • 10-week summer programme (June to September 2023)
  • 09:00-17:30 working hours
  • Based in Central London

Over the course of 10 weeks, G-Research Summer Research Programme interns gain a unique insight into life as a Machine Learning practitioner at a leading quantitative finance research firm.

Our full-time ML researchers use a wide range of tools and techniques in an applied setting, putting their expertise to use in direct, production-ready applications with immediate results.

They have access to vast computing resources and are limited only by their imagination. As an ML intern, you will have the opportunity to experience some of this as part of a 10-week programme working on a meaningful and challenging research project that demands the application of innovative yet pragmatic mathematical and computational analysis.

You will be paired with a mentor who will supervise your work and provide ongoing feedback to help you improve and develop, as well as access to senior staff who are leaders in their fields. Your internship will culminate in a final presentation of your research ideas to senior management.

Taking part in G-Research's Summer Internship Programme will give you an in-depth insight into our academic approach to the world of quantitative finance and allow you to explore the thriving city of London, while you get to know your fellow interns and colleagues through a full itinerary of fun social events.

A high percentage of our interns go on to join G-Research on a full-time basis on completion of their academic studies.

Who are we looking for?

The ideal candidate will have the following skills and experience:

  • A post-graduate degree in Machine Learning or a related discipline, or commercial experience developing novel machine learning algorithms. We will also consider exceptional candidates with a proven record of success in online data science competitions, such as Kaggle
  • Experience in one or more of deep learning, reinforcement learning, non-convex optimisation, Bayesian non-parametrics, NLP or approximate inference
  • Excellent reasoning skills and mathematical ability are crucial: off-the-shelf methods don't always work with our data, so you will need to understand how to develop your own models
  • Strong programming skills and experience working with Python, scikit-learn, SciPy, NumPy, Pandas and Jupyter

Previous experience in finance is not required, although an interest in finance and the motivation to rapidly learn more is a prerequisite for working here.

Why should you apply?

  • Highly competitive compensation plus accommodation
  • G-Research community with weekly intern activities
  • Lunch provided (via Just Eat for Business) and dedicated barista bar
  • 30 days’ annual leave pro-rated
  • Informal dress code and excellent work/life balance
  • Central London office close to 5 stations and 6 tube lines

G-Research is committed to cultivating and preserving an inclusive work environment. We are an ideas-driven business and we place great value on diversity of experience and opinions.

We want to ensure that applicants receive a recruitment experience that enables them to perform at their best. If you have a disability or special need that requires accommodation please let us know in the relevant section.

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Opportunity Overview

  • Deadline: Ongoing
  • Starting: June 2023
  • Starting Salary: Competitive + benefits
  • 2:1 and above (expected)
  • 10 weeks
  • London
    (Show map)

Preferred Disciplines...

  • Computer Science
  • Data Science
  • Maths
  • Robotics
  • Software

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