At a Glance
- Tasks: Analyse data and develop predictive models to enhance trading strategies.
- Company: Join Cubist Systematic Strategies, a leader in systematic trading.
- Benefits: Competitive salary, mentorship from experts, and career progression opportunities.
- Other info: Collaborative environment with a focus on innovation and ethical standards.
- Why this job: Make an impact in finance by transforming raw data into actionable insights.
- Qualifications: Degree in a quantitative field and programming skills in Python or SQL.
The predicted salary is between 50000 - 70000 € per year.
About Cubist
Cubist Systematic Strategies, an affiliate of Point72, deploys systematic, computer-driven trading strategies across multiple liquid asset classes, including equities, futures and foreign exchange. The core of our effort is rigorous research into a wide range of market anomalies, fueled by our unparalleled access to a wide range of publicly available data sources.
Role
Data Scientists bridge the gap between raw data and predictive modelling. We believe everything starts with data. You will work closely with our quantitative research team, applying advanced techniques to engineer, validate, and refine features that feed directly into our systematic models. This is a role within an established investment team, offering opportunities for progression into more senior research responsibilities across the full trading pipeline.
Responsibilities
- Conduct thorough data analysis under the mentorship of a senior quantitative researcher.
- Generate novel ideas for enhanced proprietary data products.
- Track and evaluate new offerings from internal and external data vendors in partnership with Compliance.
- Transform firm approved raw datasets into robust features for our systematic models.
- Build analytical tools to supplement our shared research framework.
Requirements
- BS, MS or PhD in finance, economics, mathematics, statistics, data science, computer science, or other quantitative discipline.
- Programming in Python (or a comparable language) and working knowledge of SQL.
- Strong analytical and quantitative skills.
- Willingness to take ownership of their work.
- Ability to work both independently and collaboratively within a team.
- Strong desire to deliver high quality results in a timely fashion.
- High attention to detail.
- Prior experience as a data analyst, data sourcing specialist, or data scientist for a financial firm is a plus.
- Commitment to the highest ethical standards.
Data Scientist employer: Point72 Asset Management, L.P
Cubist Systematic Strategies is an exceptional employer that fosters a collaborative and innovative work culture, where Data Scientists are empowered to bridge the gap between raw data and predictive modelling. With a strong emphasis on employee growth, you will have the opportunity to advance into senior research roles while working alongside a talented quantitative research team in a dynamic environment. Located in a vibrant financial hub, we offer access to unparalleled resources and a commitment to ethical standards, making it a rewarding place for those seeking meaningful contributions in the world of finance.
Contact Detail:
Point72 Asset Management, L.P Recruiting Team
StudySmarter Expert Advice🤫
We think this is how you could land Data Scientist
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Cubist through LinkedIn. A friendly chat can give us insider info and might just get our foot in the door.
✨Tip Number 2
Show off our skills! Prepare a portfolio showcasing our data analysis projects, especially those using Python and SQL. This will help us stand out during interviews and demonstrate our hands-on experience.
✨Tip Number 3
Practice makes perfect! Get comfortable with common data science interview questions and case studies. We can even do mock interviews with friends to boost our confidence before the big day.
✨Tip Number 4
Apply directly through our website! It’s the best way to ensure our application gets seen by the right people. Plus, it shows we’re genuinely interested in joining the team at Cubist.
We think you need these skills to ace Data Scientist
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Data Scientist role. Highlight your experience with data analysis, programming in Python, and any relevant projects that showcase your analytical skills. We want to see how your background aligns with what we do!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about data science and how you can contribute to our team. Be sure to mention any specific experiences that relate to systematic trading or quantitative research.
Showcase Your Projects:If you've worked on any interesting data projects, don’t hold back! Include links to your GitHub or any portfolios that demonstrate your skills in transforming raw data into actionable insights. We love seeing practical applications of your work!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team at Cubist!
How to prepare for a job interview at Point72 Asset Management, L.P
✨Know Your Data Inside Out
Make sure you’re well-versed in the datasets relevant to the role. Familiarise yourself with common data sources and be ready to discuss how you would transform raw data into actionable insights. This shows your understanding of the core responsibilities.
✨Brush Up on Your Programming Skills
Since programming in Python and SQL is crucial for this role, practice coding problems related to data manipulation and analysis. Be prepared to demonstrate your skills during the interview, as practical examples can really set you apart.
✨Showcase Your Analytical Mindset
Prepare to discuss past projects where you applied analytical techniques. Highlight how you generated novel ideas or improved existing processes. This will illustrate your ability to think critically and contribute to the team’s goals.
✨Emphasise Team Collaboration
This role requires both independent work and teamwork. Share experiences where you successfully collaborated with others, especially in a research or data-driven environment. It’s important to show that you can thrive in a team setting while also taking ownership of your tasks.
