Alternative Data Scientist

A leading global trading firm is expanding its alternative data initiative and is seeking an experienced Data Scientist to help drive the next phase of signal discovery and deployment. Sitting at the intersection of quantitative research and live trading, you’ll work with datasets that are large, messy and unstructured - using rigorous analytical methods to determine what is predictive, what scales, and what ultimately makes it into production.

The team operates in a research-driven environment with fast feedback loops, close proximity to trading, and a strong emphasis on measurable impact rather than theoretical modelling.

• Evaluate and analyse a wide range of alternative datasets (transactional, behavioural, geospatial, web-derived, etc.) to identify potential trading signals
• Design and run experiments to assess data quality, stability, coverage and predictive power
• Build statistical and machine learning models to transform raw alternative data into usable features and signals
• Develop robust analytical frameworks to monitor signal decay, bias and performance over time
• Communicate findings clearly to quantitative researchers and key stakeholders, influencing research and trading priorities

• A strong academic background in a quantitative field from a top-tier university
• 2–5 years of experience in a data science or research role within a hedge fund, market maker, or investment bank
• Demonstrated experience working with alternative data and assessing its real-world usefulness
• Advanced Python skills and strong SQL capability for large-scale data analysis
• A solid understanding of statistics, experimentation, and applied machine learning in noisy environments