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- Tasks: Originate and analyse datasets, build predictive models, and deliver insights for investment decisions.
- Company: Newly launched hedge fund focused on the global Industrials sector.
- Benefits: Competitive salary, collaborative environment, and opportunity to shape data science capabilities.
- Why this job: Make an immediate impact on investment strategies and work with a talented team.
- Qualifications: Strong Python and SQL skills, experience in advanced analytics or ML, and a quantitative background.
- Other info: Dynamic role with opportunities for growth as the firm expands.
The predicted salary is between 36000 - 60000 £ per year.
A newly launched long/short hedge fund specialising in the global Industrials sector is seeking a Data Scientist to help shape its data-driven investment strategy. The firm combines fundamental research with advanced data science, building scalable infrastructure where insights directly influence portfolio performance.
The Data Scientist will originate and analyse novel datasets, build predictive models, and deliver insights that drive investment decisions. The position involves working closely with investors and engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure.
Key Requirements
- Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills
- Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal)
- Proficiency with BI tools (Tableau or similar)
- 2–6 years’ relevant experience and a strong quantitative background
- Ability to source and structure new datasets and collaborate across disciplines
Opportunity
This role offers the chance to make an immediate impact on investment decisions, collaborate with an experienced investment and technology team, and push the boundaries of data-driven investing. As the firm grows, the Data Scientist will have the opportunity to shape and expand its data science capability.
Data Scientist - Hedge Fund (New-Launch) employer: Radley James
Contact Detail:
Radley James Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Hedge Fund (New-Launch)
✨Tip Number 1
Network like a pro! Reach out to people in the hedge fund and data science space on LinkedIn. Join relevant groups and participate in discussions to get your name out there.
✨Tip Number 2
Showcase your skills! Create a portfolio of projects that highlight your Python, SQL, and machine learning expertise. Share these on GitHub or your personal website to impress potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on your technical skills and understanding the hedge fund landscape. Practice common data science interview questions and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’re always looking for talented individuals who can contribute to our data-driven investment strategies. Your next big opportunity could be just a click away!
We think you need these skills to ace Data Scientist - Hedge Fund (New-Launch)
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your strong Python and SQL skills in your application. We want to see how you've applied advanced analytics or machine learning in real-world scenarios, especially in finance or forecasting contexts.
Tailor Your Experience: When writing your application, tailor it to reflect your experience with BI tools like Tableau. We’re looking for someone who can build predictive models and deliver insights, so make sure to showcase relevant projects you've worked on.
Be Data-Driven: Since we’re all about data-driven decision-making, include specific examples of how your work has influenced investment strategies or outcomes. This will help us see the impact you could have on our team.
Apply Through Our Website: Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity to shape our data science capability.
How to prepare for a job interview at Radley James
✨Know Your Data Science Tools
Make sure you brush up on your Python skills, especially with libraries like pandas, NumPy, and scikit-learn. Be ready to discuss how you've applied these tools in real-world scenarios, particularly in finance or forecasting contexts.
✨Showcase Your Analytical Mindset
Prepare examples of how you've used advanced analytics or machine learning to solve complex problems. Think about specific projects where your insights directly influenced outcomes, and be ready to explain your thought process.
✨Familiarise Yourself with BI Tools
If you have experience with BI tools like Tableau, make sure to highlight it. Be prepared to discuss how you've used these tools to create dashboards or visualisations that helped stakeholders understand data better.
✨Collaborate and Communicate
Since this role involves working closely with investors and engineers, think about times when you've successfully collaborated across disciplines. Be ready to share how you communicate complex data insights to non-technical team members.