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- Tasks: Analyse data and create features for trading models while collaborating with experienced researchers.
- Company: Global investment firm focused on innovation and teamwork.
- Benefits: Competitive salary, mentorship opportunities, and a dynamic work environment.
- Why this job: Join a cutting-edge team and make an impact in the finance world through data science.
- Qualifications: Quantitative degree, Python programming skills, and strong analytical mindset.
- Other info: Exciting career growth potential in a fast-paced industry.
The predicted salary is between 36000 - 60000 £ per year.
A global investment firm is seeking a Data Scientist to bridge the gap between raw data and predictive modelling. The role involves thorough data analysis under the mentorship of senior researchers, generating innovative ideas for data products, and transforming datasets into features for systematic models.
Candidates should have a quantitative degree, programming skills in Python, and strong analytical abilities. There is a strong emphasis on teamwork and quality results in a timely manner.
Quant Data Scientist: Build Features for Trading in London employer: Point72
Contact Detail:
Point72 Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Quant Data Scientist: Build Features for Trading in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the investment and data science fields on LinkedIn. Join relevant groups and engage in discussions to get your name out there and show off your passion for data.
✨Tip Number 2
Prepare for those interviews! Brush up on your Python skills and be ready to discuss how you've used data analysis to solve real-world problems. Practice explaining your thought process clearly, as teamwork is key in this role.
✨Tip Number 3
Showcase your projects! Create a portfolio that highlights your best work in predictive modelling and feature engineering. This will give you an edge and demonstrate your ability to turn raw data into actionable insights.
✨Tip Number 4
Don’t forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your quantitative background and analytical skills, and let’s get you on board!
We think you need these skills to ace Quant Data Scientist: Build Features for Trading in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your programming skills in Python and any relevant quantitative experience. We want to see how you can bridge the gap between raw data and predictive modelling, so don’t hold back!
Be a Team Player: Since teamwork is key for us, mention any collaborative projects you've worked on. Share how you contributed to achieving quality results together with your team.
Innovate and Inspire: We love innovative ideas! If you've generated unique data products or features in the past, be sure to include those examples. Show us how you think outside the box!
Apply Through Our Website: To make sure your application gets the attention it deserves, apply directly through our website. It’s the best way for us to connect and get to know you better!
How to prepare for a job interview at Point72
✨Know Your Data Inside Out
Make sure you’re well-versed in the datasets relevant to trading and predictive modelling. Brush up on your data analysis skills and be ready to discuss how you would transform raw data into actionable features for systematic models.
✨Show Off Your Python Skills
Since programming in Python is key for this role, prepare to demonstrate your coding abilities. You might be asked to solve a problem on the spot, so practice common data manipulation tasks and be ready to explain your thought process.
✨Emphasise Teamwork
This role requires collaboration with senior researchers, so highlight your experience working in teams. Share examples of how you’ve contributed to group projects and how you handle feedback and mentorship.
✨Innovate and Ideate
Be prepared to discuss innovative ideas for data products. Think about potential improvements or new features you could bring to the table, and don’t hesitate to share your creative solutions during the interview.
