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- Tasks: Originate and analyse datasets, build predictive models, and deliver insights for investment decisions.
- Company: Newly launched hedge fund specialising in 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, SQL skills, and experience in advanced analytics or ML.
- Other info: Dynamic role with potential for career 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
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 (Python, ML, SQL) employer: Radley James
Contact Detail:
Radley James Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist (Python, ML, SQL)
✨Tip Number 1
Network like a pro! Reach out to professionals in the hedge fund and data science space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational interviews. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your Python projects, predictive models, and any real-world applications of ML you've worked on. This is your chance to demonstrate how you can drive investment decisions with data—make it shine!
✨Tip Number 3
Prepare for those interviews! Brush up on your SQL queries and be ready to discuss your experience with BI tools like Tableau. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both investors and engineers.
✨Tip Number 4
Apply through our website! We’re always on the lookout for talented Data Scientists who can help shape our data-driven investment strategy. Don’t miss out on the opportunity to make an impact—submit your application today!
We think you need these skills to ace Data Scientist (Python, ML, SQL)
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 the key requirements mentioned in the job description. Share specific examples of your experience with BI tools like Tableau and how you've collaborated across disciplines.
Be Data-Driven: Since we're all about data-driven insights, include any relevant projects where you sourced and structured new datasets. This will show us your ability to originate and analyse novel datasets, which is crucial for this role.
Apply Through Our Website: We encourage you to apply through our website for a smoother process. It helps us keep track of your application and ensures you don’t miss out on any updates from us!
How to prepare for a job interview at Radley James
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python, SQL, and any ML frameworks mentioned in the job description. Brush up on libraries like pandas, NumPy, and scikit-learn, and be ready to discuss how you've applied them in real-world scenarios, especially in finance or forecasting.
✨Showcase Your Analytical Skills
Prepare to discuss specific projects where you’ve built predictive models or analysed datasets. Be ready to explain your thought process, the challenges you faced, and how your insights influenced decisions. This will demonstrate your ability to drive investment strategies.
✨Familiarise Yourself with BI Tools
Since proficiency with BI tools like Tableau is a key requirement, make sure you can talk about your experience with these tools. If you have examples of dashboards you've created or insights you've visualised, bring those to the table!
✨Collaboration is Key
This role involves working closely with investors and engineers, so be prepared to discuss your experience collaborating across disciplines. Highlight any teamwork experiences that showcase your ability to communicate complex data insights effectively.
