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- Tasks: Build and test machine learning models for trading strategies in a fast-paced environment.
- Company: Join Jane Street, a leading global trading firm known for innovation and collaboration.
- Benefits: Enjoy flexible work options, competitive pay, and opportunities for professional growth.
- Why this job: Be part of a dynamic team shaping the future of machine learning in finance.
- Qualifications: Deep ML experience, strong communication skills, and a passion for problem-solving required.
- Other info: Opportunity to influence hiring, attend conferences, and teach techniques to teammates.
The predicted salary is between 48000 - 72000 £ per year.
Machine learning is a critical pillar of Jane Street's global business, and our ever-changing trading environment serves as a unique, rapid-feedback platform for ML experimentation. Researchers at Jane Street are responsible for building models, strategies, and systems that price and trade a variety of financial instruments. This work involves analyzing large datasets, building and testing models, creating new trading strategies, and writing the code that implements them.
We’re looking for people to join the research team with deep ML experience in either an applied or academic context. A good candidate should have a deep understanding of a wide variety of ML techniques, and a passion for tinkering with model architectures, feature transformations, and hyperparameters to generate robust inferences. We also want people who are good communicators, with the ability to quickly absorb the context of a new problem, carefully consider tradeoffs, and recommend possible solutions.
As an ML researcher, your expertise will also shape the firm’s future ML developments including hiring new ML researchers, attending conferences, teaching techniques to teammates, and setting firmwide goals.
Contact Detail:
Jane Street Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Researcher
✨Tip Number 1
Familiarise yourself with the specific ML techniques mentioned in the job description. Make sure you can discuss your experience with these methods in detail, as this will show your deep understanding and passion for the field.
✨Tip Number 2
Prepare to demonstrate your problem-solving skills during the interview. Think of examples where you've tackled complex ML problems, and be ready to explain your thought process and the trade-offs you considered.
✨Tip Number 3
Showcase your communication skills by being clear and concise when discussing your past projects. Practice explaining complex concepts in simple terms, as this will highlight your ability to convey ideas effectively.
✨Tip Number 4
Engage with the ML community by attending relevant conferences or meetups. This not only helps you stay updated on industry trends but also provides networking opportunities that could lead to valuable connections at Jane Street.
We think you need these skills to ace Machine Learning Researcher
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with machine learning techniques, projects you've worked on, and any relevant academic achievements. Use specific examples to demonstrate your skills in building models and analysing datasets.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and how it relates to the financial sector. Discuss your problem-solving approach and how you can contribute to Jane Street's research team. Be sure to mention any relevant experiences that showcase your communication skills.
Showcase Your Projects: If you have worked on notable machine learning projects, consider including a portfolio or links to your work. This could be GitHub repositories or published papers that demonstrate your ability to build and test models effectively.
Prepare for Technical Questions: Anticipate technical questions related to machine learning algorithms, model evaluation, and coding challenges. Brush up on your knowledge of various ML techniques and be ready to discuss your thought process in tackling complex problems.
How to prepare for a job interview at Jane Street
✨Showcase Your ML Expertise
Be prepared to discuss your experience with various machine learning techniques. Highlight specific projects where you've applied these methods, and be ready to explain the outcomes and any challenges you faced.
✨Demonstrate Problem-Solving Skills
During the interview, expect to tackle hypothetical scenarios or case studies. Practice articulating your thought process clearly, considering trade-offs, and proposing well-reasoned solutions to complex problems.
✨Communicate Effectively
Since good communication is key for this role, practice explaining technical concepts in a way that’s accessible to non-experts. This will show your ability to collaborate with diverse teams and share your insights effectively.
✨Prepare for Technical Questions
Brush up on your coding skills and be ready to solve technical problems on the spot. Familiarise yourself with common algorithms and data structures, as well as the tools and languages relevant to machine learning.
