Data Scientist

Our client is a leading systematic trading firm seeking a Data Scientist to join a highly collaborative Data Analytics team working at the intersection of Quantitative Research, Trading, and Engineering.

The team plays a central role in identifying, extracting, structuring, and scaling datasets used across systematic trading strategies and discretionary investment workflows. This is a highly technical and research-driven environment where data quality, speed of onboarding, and analytical insight directly impact investment decision-making.

The successful candidate will work closely with Quantitative Researchers and Traders to design and build datasets that support alpha generation, market analysis, and trading strategy development. The role combines elements of data engineering, quantitative research, and large-scale data processing within a fast-paced buy-side environment.

Key Responsibilities

• Collaborate with Quantitative Researchers and Traders to develop datasets used across systematic and discretionary trading strategies
• Design and prototype scalable data extraction, cleaning, transformation, and aggregation workflows across a wide range of raw and unstructured data sources
• Build and optimise robust Python-based tooling and data pipelines for onboarding new datasets into production environments
• Work closely with Engineering teams to automate and scale data ingestion and processing systems
• Manage the end-to-end lifecycle of alternative and traditional financial datasets
• Investigate and solve complex data quality and data availability challenges to minimise time-to-production
• Research and experiment with novel data extraction and enrichment techniques to improve the firm’s broader data capabilities
• Contribute to a highly collaborative environment spanning Research, Trading, Engineering, and external data vendors

Requirements

• 3+ years of experience within Data Science, Quantitative Data Engineering, Research Engineering, or similar technical roles
• Strong Python programming skills, including experience with libraries such as Pandas and NumPy
• Experience working with large-scale structured and unstructured datasets
• Strong interest in financial markets and the application of data within trading and investment workflows
• Experience working with traditional and/or alternative financial datasets
• Excellent communication skills and the ability to work closely with technical and non-technical stakeholders
• Ability to operate effectively within a high-performance, high-velocity environment

Preferred Background

• Buy-side quantitative finance experience
• Experience supporting systematic trading or quantitative research environments
• Exposure to alternative data, NLP, web scraping, entity resolution, or large-scale data processing
• Academic background in Mathematics, Physics, Engineering, Computer Science, or another quantitative discipline

This is an opportunity to join a highly technical and data-driven trading environment where the successful candidate will have direct impact on research, trading, and investment workflows across the business.