At a Glance
- Tasks: Apply advanced data modelling and statistical methods to market prediction and trading.
- Company: Join a leading firm in finance and technology, shaping the future of trading.
- Benefits: Gain hands-on experience, mentorship, and potential career opportunities in finance.
- Other info: Collaborative team environment with a focus on innovation and growth.
- Why this job: Make an impact in financial markets while developing your analytical skills.
- Qualifications: Pursuing a degree in finance, computer science, or a related quantitative field.
The predicted salary is between 20000 - 30000 £ per year.
This is an opportunity for students and researchers of advanced data modeling and statistical learning methods to apply these techniques to market prediction and systematic trading.
Job Responsibilities:
- Pre-process (validate, clean, normalize, reduce dimension) very large data sets for model estimation and event studies
- Identify features and relationships useful for the predictive modeling of market dynamics
Desirable Candidates:
- Undergraduate, MS, or PhD candidates in finance, computer science, mathematics, physics, or other quantitative discipline
- Programming in any of the following: C++, Java, C#, MATLAB, R, Python, or Perl
- Strong analytical and quantitative skills
- Demonstrated interest in financial markets and systematic trading
- Clear, concise, and proactive communicator
- Detail-oriented
- Willing to take ownership of his/her work, working both independently and within a small team
Quantitative Researcher - Intern employer: Point72 Asset Management, L.P
As a leading firm in quantitative research, we offer an exceptional environment for interns to thrive, with access to cutting-edge data modeling techniques and a collaborative work culture that fosters innovation. Our commitment to employee growth is evident through mentorship opportunities and hands-on experience in market prediction, making this internship not just a job, but a stepping stone to a rewarding career in finance and technology.
Contact Details:
Point72 Asset Management, L.P Recruitment Team
StudySmarter Expert Advice🤫
We think this is how you could land Quantitative Researcher - Intern
✨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 Quantitative Researcher - Intern
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 Point72 Asset Management, L.P 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 Point72 Asset Management, L.P
✨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 Point72 Asset Management, L.P.
✨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 Point72 Asset Management, L.P that you’re not just looking for experience, but that you're keen to contribute and grow within the team.
