London Summer Data Science Internship — Research & ML

London Summer Data Science Internship — Research & ML

Internship 22500 - 27500 £ / year (est.) No working from home possible
PVH (Tommy Hilfiger/Calvin Klein)

At a Glance

  • Tasks: Apply Python, statistics, and ML to real datasets in finance.
  • Company: G-Research, a leader in data science and finance.
  • Benefits: Accommodation provided, 30 days leave pro-rated, and hands-on experience.
  • Other info: Rigorous 10-week programme based in vibrant Central London.
  • Why this job: Gain invaluable experience working with top data scientists and financial experts.
  • Qualifications: Open to quantitative undergraduates to PhD students with a passion for data science.

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

G-Research is offering a 10-week Summer Research Programme in London, inviting quantitative-undergraduate to PhD students to explore data science in finance. The role involves applying Python, statistics and ML to real datasets, supporting data creation and tooling, and collaborating with leading data scientists and financial experts.

Based in Central London, the internship includes a rigorous schedule with 09:00-17:30 hours, and benefits such as accommodation and 30 days leave pro-rated.

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London Summer Data Science Internship — Research & ML employer: PVH (Tommy Hilfiger/Calvin Klein)

Intapp is an exceptional employer, offering a dynamic work environment that fosters innovation and collaboration within the accounting and consulting sectors across EMEA. With a strong commitment to employee growth, Intapp provides ample opportunities for professional development and leadership coaching, ensuring that team members thrive in their careers while contributing to the company's strategic vision. The culture is built on accountability and high performance, making it an ideal place for those looking to make a significant impact in a rapidly evolving industry.

PVH (Tommy Hilfiger/Calvin Klein)

Contact Details:

PVH (Tommy Hilfiger/Calvin Klein) Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land London Summer Data Science Internship — Research & ML

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.

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 PVH (Tommy Hilfiger/Calvin Klein) 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 PVH (Tommy Hilfiger/Calvin Klein)

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 PVH (Tommy Hilfiger/Calvin Klein).

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 PVH (Tommy Hilfiger/Calvin Klein) that you’re not just looking for experience, but that you're keen to contribute and grow within the team.