At a Glance
- Tasks: Collaborate with ML Researchers on innovative projects in systematic trading.
- Company: Join Jane Street, a leader in finance and technology.
- Benefits: Gain hands-on experience, access to vast data, and cutting-edge tech.
- Other info: Dynamic environment with opportunities for growth and learning.
- Why this job: Dive into real-world challenges and make an impact in finance.
- Qualifications: Undergraduate or PhD student with ML experience and a curious mindset.
The predicted salary is between 50000 - 70000 £ per year.
Our goals are to give you a real sense of what it's like to work at Jane Street as a Machine Learning Researcher while also providing a truly unparalleled educational experience. You'll work side by side with experienced ML Researchers on projects that we've selected for their combination of novel ML ideas and relevance to real-world systematic trading strategies. You'll learn how we think about markets through challenging classes and activities, and practice using established methods alongside our own unique twists to train practical models.
At Jane Street, the lines between research, technology, and trading are intentionally blurry, and you’ll have access to petabytes of data, a computing cluster with hundreds of thousands of cores, and a growing GPU cluster containing 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. You'll spend the bulk of your internship working closely with full-time machine learning researchers on projects drawn from their own work. You might conduct an end-to-end study of an unexplored dataset, try a new modeling paradigm for a thorny problem, or consider blue-sky approaches that we're still trying to figure out.
The problems we work on rarely have clean, definitive answers, and they often require insights from colleagues across the firm with different areas of expertise. Depending on the day, you might be diving deep into market data, tuning hyperparameters, debugging training issues, or analyzing the predictions your model makes. Note that given the IP-sensitive nature of machine learning research at Jane Street, it is unlikely that any research findings associated with the internship will be suitable for outside academic publication.
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. We're more interested in how you think and learn than what you currently know.
You should be:
- An undergraduate, PhD student, or postdoc with practical experience working on ML problems
- Interested in applying logical and mathematical thinking to all kinds of problems
- Curious about the machine learning landscape and excited to apply state-of-the-art techniques drawn from many problem domains
- Fluent with a versatile set of models and tricks
- Able to rapidly implement and iterate on your ideas in Python and your favourite ML framework
- Eager to ask questions, admit mistakes, and learn new things
If you'd like to learn more, you can read about our interview process and meet some of the team. Learn more about Jane Street's internship program here.
ꓟachine ꓡearning ꓣesearcher in London employer: Jane Street
At Jane Street, we pride ourselves on being an exceptional employer, offering a unique blend of cutting-edge machine learning research and real-world trading applications. Our collaborative work culture fosters innovation and continuous learning, providing interns with unparalleled access to vast datasets and advanced computing resources. With a focus on personal and professional growth, you'll have the opportunity to work alongside experienced researchers, tackling complex challenges that push the boundaries of machine learning in finance.
StudySmarter Expert Advice🤫
We think this is how you could land ꓟachine ꓡearning ꓣesearcher in London
✨Join Data-Science Meetups
Get yourself along to local data-science meetups or workshops. They're goldmines for networking, and you'll learn from industry pros who might just point you in the direction of internships. Plus, discussing the latest trends with like-minded individuals can really amp up your game.
✨Utilise University Career Services
Check in with your uni's career services since they often have connections with companies looking for interns. They might even organise information sessions with firms, which can be a great chance for you to learn more about potential internships and make some key contacts.
✨Show Off Your Stuff on GitHub
If you're into data science, having a GitHub profile with your projects is essential. Make sure your portfolio is public and showcases your best work! Recruiters love to see your coding skills and problem-solving approach, and it’s a brilliant way to stand out.
✨Apply Directly on Our Website
Don’t forget to check out the internships listed on our site! It's always a good idea to apply directly through our website because it makes your application easier for our team to find, and you might just catch the hiring manager’s eye by showcasing exactly what you're passionate about in data science.
We think you need these skills to ace ꓟachine ꓡearning ꓣesearcher in London
Some tips for your application 🫡
Show Off Your Technical Skills:For a data science internship, we want to see those analytical skills shine! List your programming languages, like Python or R, and make sure to highlight any relevant projects or courses you've completed. If you've dabbled with tools like Pandas, NumPy, or machine learning algorithms, don’t hold back – include those in your CV!
Share Your Curiosity in Your Cover Letter:As an intern, your motivation and eagerness to learn are key! In your cover letter, talk about specific data science concepts that excite you and how this internship at Jane Street will help you grow. Share what you hope to achieve and how you plan to tackle real-world data problems - we love enthusiasm!
Include Any Relevant Certifications:If you've earned any certifications, such as from Coursera or DataCamp, make sure to include these in your application. They show us that you're proactive and committed to expanding your data science skillset. This could make a real difference in how we assess your application!
Keep It Relevant and Concise:Remember, as an intern, you don’t need to have decades of experience. Focus on showcasing relevant coursework, personal projects, or even related volunteer work in data science. Keep your CV and cover letter concise but impactful – we appreciate clear and straightforward communication!
How to prepare for a job interview at Jane Street
✨Brush Up on Your Coding Skills
As a data science intern, you might get grilled on your programming skills. Expect to tackle some coding challenges using languages like Python or R. We recommend practising basic algorithms or data manipulation tasks so you can show off your tech skills with confidence.
✨Show Off Your Projects
Prepare to discuss any projects you’ve done, whether in your studies or on your own time. Having a strong portfolio of data analyses or machine learning models will really set you apart. We can use platforms like GitHub to showcase your work to impress Jane Street.
✨Know Your Stats and ML Basics
Brush up on your statistics and machine learning concepts because interviewers love to dig into this! Be ready to explain your understanding of algorithms or how you would approach a given data problem. This will highlight your theoretical background alongside your practical skills.
✨Be Eager to Learn and Adapt
Internships are all about potential and growth. Make sure you convey your eagerness to learn and adapt to new tools or methodologies. Show Jane Street that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
