ML Researcher Intern: Real-World, Large-Scale Models in London

ML Researcher Intern: Real-World, Large-Scale Models in London

London Internship 22500 - 27500 £ / year (est.) No working from home possible
Trading Interview

At a Glance

  • Tasks: Collaborate with senior researchers on innovative ML projects and tackle real-world challenges.
  • Company: Jane Street, a leading firm in trading and technology.
  • Benefits: Gain hands-on experience, access to cutting-edge resources, and mentorship from experts.
  • Other info: Dynamic internship with opportunities for growth and learning.
  • Why this job: Dive into the world of machine learning and make an impact in trading.
  • Qualifications: Passion for ML, problem-solving skills, and a collaborative mindset.

The predicted salary is between 22500 - 27500 £ per year.

Jane Street is offering an internship for a Machine Learning Researcher.

You will work alongside senior ML researchers on projects chosen for their mix of novel ML ideas and practical trading relevance.

Expect to access very large datasets, a clustered computing environment, and GPU resources while learning through challenging classes and hands-on practice.

The role emphasizes problem solving, collaboration, and iterative experimentation.

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ML Researcher Intern: Real-World, Large-Scale Models in London employer: Trading Interview

Tower Research Capital is an exceptional employer that fosters a dynamic and collaborative work culture, where innovation and rigorous experimentation are at the forefront. Located in a vibrant financial hub, employees benefit from cutting-edge technology and resources, alongside ample opportunities for professional growth and development within the fast-paced world of quantitative trading. Join us to be part of a team that values your contributions and rewards your success in a meaningful way.

Trading Interview

Contact Details:

Trading Interview Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land ML Researcher Intern: Real-World, Large-Scale Models 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 ML Researcher Intern: Real-World, Large-Scale Models in London

Machine Learning
Data Analysis
Problem Solving
Collaboration
Iterative Experimentation
Large-Scale Data Handling
Clustered Computing

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 Trading Interview 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 Trading Interview

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 Trading Interview.

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 Trading Interview that you’re not just looking for experience, but that you're keen to contribute and grow within the team.