At a Glance
- Tasks: Join our team to build deep learning models for trading strategies using cutting-edge technology.
- Company: Dynamic finance firm with a collaborative and innovative culture.
- Benefits: Competitive salary, opportunities for growth, and a chance to attend conferences.
- Other info: Work closely with traders and researchers in a fast-paced, supportive environment.
- Why this job: Make a real impact in finance by solving complex ML problems with a curious team.
- Qualifications: Experience in machine learning, coding skills in Python, and a passion for problem-solving.
The predicted salary is between 63000 - 77000 £ per year.
We’re looking for smart and curious individuals from industry and academia to join our growing team and drive our ML work. On our Machine Learning team, you'll build the deep learning models that power our trading strategies, supported by our rapidly growing computing cluster with tens of thousands of high-end GPUs. Trading poses unusual challenges—large models and nonstationary datasets in a competitive multi-agent environment that force us to search for novel techniques. Researchers, engineers and traders sit a few feet away from each other and work together to train models, architect systems and run trading strategies.
Depending on the day, we might be diving deep into market data, tuning hyperparameters, debugging distributed training performance or studying how our model likes to trade in production. We’ll rely on your in-depth knowledge of the machine learning landscape and understanding of a variety of approaches—drawn from LLMs, image models, RL agents, recommendation systems or classical ML methods to shape the future of ML at Jane Street. You’ll train models for the next generation of our deep learning-based trading strategies, and build the fundamental understanding we need to tackle new markets and situations. You’ll also be hiring new colleagues, attending conferences and teaching techniques to teammates—all of which we consider to be real and impactful parts of the job.
If you’ve never thought about a career in finance, you’re in good company. Many of us were in the same position before working here. If you have a curious mind and a passion for solving interesting problems, we have a feeling you’ll fit right in. There’s no fixed set of skills we are looking for, but you should bring:
- Practical experience working on empirical ML problems
- The ability to apply logical and mathematical thinking to all kinds of problems
- Intellectual curiosity and excitement about state-of-the-art research across many ML problem domains
- Fluency with a versatile set of models and tricks
- The hands-on coding skills needed to rapidly implement and iterate on your ideas, in Python and your favourite ML framework
- An eagerness to ask questions, admit mistakes and learn new things
- Fluency in English
Machine Learning Researcher employer: Janestreet
Jane Street is an exceptional employer located in Greater London, offering a dynamic work culture that fosters collaboration and innovation. Employees benefit from engaging projects in finance tech, opportunities for professional growth, and a commitment to using cutting-edge technology. With a focus on intellectual curiosity and teamwork, Jane Street provides a rewarding environment for those passionate about software engineering.
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We think this is how you could land Machine Learning Researcher
✨Get Involved in Data Science Meetups
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Janestreet.
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We think you need these skills to ace Machine Learning Researcher
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Janestreet, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Janestreet. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Janestreet
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Janestreet!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
