Data Scientist | Equity (L / S) Hedge Fund

Selby Jennings; City Of London; On-site; GBP 60,000 - 85,000; Full time

Job summary

A newly launched hedge fund is seeking a Data Scientist to join its investment team in London. This role focuses on applying data science to generate insights that drive portfolio performance. Key responsibilities include building predictive models, managing datasets, and designing dashboards. Candidates should have 3+ years of experience in advanced analytics, strong Python and SQL skills, and a relevant quantitative degree. This is a unique opportunity to help shape a data science capability while working directly with experienced investment professionals.

Qualifications

• 3+ years' experience applying advanced analytics or ML to real-world data.
• Experience in finance, supply chain, or predictive modeling contexts.
• Ability to source and leverage new datasets.

Responsibilities

• Originate and evaluate novel datasets and manage onboarding of new vendors.
• Collaborate with the investment team to translate hypotheses into data-driven projects.
• Build predictive models for company KPIs using econometrics and machine learning.
• Design and maintain dashboards to monitor fundamentals.
• Apply AI/ML techniques to link and organize datasets.

Skills

Python skills

SQL

Advanced analytics

Machine learning

Statistical methods

Communication skills

Education

Degree in Math, Physics, Computer Science, Econometrics, or related fields

Tools

pandas

NumPy

scikit-learn

Tableau

Job description

A newly launched long / short hedge fund is seeking a Data Scientist to join its investment team. This is a high-impact role where applied data science is central to generating differentiated insights and driving portfolio performance.

About the Role

You'll work closely with investors and engineers to source, structure, and analyze real-world datasets, build predictive models, and create outputs that directly inform investment decisions. The role combines data origination with advanced analytics - expect to work with large-scale alternative data, develop KPI forecasting models, and design dashboards that track fundamentals in real time.

Key Responsibilities

• Originate and evaluate novel datasets (e.g., supply chain, geospatial, IoT, pricing, web activity) and manage onboarding of new vendors.
• Collaborate with the investment team to translate hypotheses into data-driven projects with measurable impact.
• Build predictive models for company KPIs using econometrics, statistical methods, and machine learning.
• Design and maintain dashboards to monitor fundamentals and calibrate investment theses.
• Work with engineers to integrate models and dashboards into a scalable data platform.
• Apply AI / ML techniques (e.g., NLP, knowledge graphs) to link and organize datasets across companies and sectors.

Ideal Candidate Profile

• Strong Python skills (pandas, NumPy, scikit-learn; familiarity with PyTorch / TensorFlow a plus).
• Proficiency in SQL and experience handling large datasets; Tableau or similar BI tools for dashboards.
• 3+ years' experience applying advanced analytics or ML to real-world data, ideally in finance, supply chain, or predictive modeling contexts.
• Strong quantitative background (Math, Physics, Computer Science, Econometrics, or related fields).
• Demonstrated ability to source and leverage new datasets, not just standard financials.
• Excellent communication skills and ability to collaborate across investment and technical teams.

Why This Role Is Exciting

You'll have direct exposure to the founders, CIO, senior traders, and heads of key functions - giving you unparalleled insight into investment strategy and decision-making. This is a rare opportunity to shape a data science capability from the ground up while working alongside some of the most respected professionals in the industry.

Apply today!