Quantitative Researcher

Radley James; Greater London; On-site; GBP 80,000 - 120,000; Full time

Job summary

London-based hedge fund is seeking a Data Scientist / Quantitative Researcher to generate alpha from alternative data sources. You will explore, structure, and analyze novel datasets, develop predictive models, and collaborate with engineers and portfolio managers to move research into production.

Key responsibilities include sourcing diverse data, building and validating models, and developing end-to-end data pipelines for backtesting and deployment.

Qualifications

• Experience building quantitative models from alternative datasets.
• Strong programming skills in Python and data manipulation.
• Ability to design and maintain data pipelines for backtesting and production.
• Collaborate with engineers and portfolio managers to deploy research.

Responsibilities

• Source, clean, and structure alternative datasets (web, geospatial, satellite, ESG, etc.) for research purposes.
• Develop and validate quantitative models to extract alpha signals.
• Build robust data pipelines for feature generation, backtesting, and analysis.
• Collaborate with engineers to translate research into deployable strategies.
• Work with portfolio managers to align research with trading goals.

Skills

Data analysis

Quant research

Python

Data pipelines

Tools

Python

SQL

Pandas

Scikit-learn

Job description

I’m working with a newly launched, research-driven hedge fund in London that is building a systematic investment platform from scratch. The fund’s edge comes from leveraging alternative and traditional datasets to identify alpha across global markets. This is a unique chance to be an early member of the research team, helping shape the data and research strategy at the ground level.

The fund is looking for a Data Scientist / Quantitative Researcher to generate alpha from alternative data sources. You’ll explore, structure, and analyze novel datasets, develop predictive models, and collaborate with engineers and portfolio managers to move research into production.

• Source, clean, and structure alternative datasets (web, geospatial, transactional, satellite, ESG, consumer, etc.) for research purposes.
• Develop and validate quantitative models to extract alpha signals.
• Build robust data pipelines for feature generation, backtesting, and analysis.
• Collaborate with engineers to ensure research translates into deployable strategies.
• Work closely with portfolio managers to align research with trading goals.