The Role

You will join a high-impact team responsible for building the next generation of data validation, quality, and integration systems that underpin systematic research and production trading. This is a hands-on senior role combining deep technical capability with sound judgement, ownership and the ability to define ‘what good looks like’.

Working closely with quantitative researchers, you will design and implement a robust framework for validating, reconciling, enriching, and integrating market-data sources across intraday and end-of-day datasets. The work spans regression testing, feature engineering, statistical analysis, and scaling high-volume pipelines that feed backtesting, alpha research and live trading systems.

The environment is collaborative and delivery-focused and you will play a key part in setting technical direction, influencing standards and mentoring peers while helping the team expand into new markets..

Key Skills and Experience Required

• ~7 years’ experience in data science, quantitative data engineering, or research data roles within trading, systematic investing, or a similarly complex data environment.
• Strong capability in Python, including production-grade development, OO design, testing, and monitoring.
• Demonstrated experience with time series analysis and statistical techniques used for data validation, quality testing, and behavioural analysis between datasets.
• Expertise working with market data, ideally including options datasets, Greeks, intraday series (hourly or higher frequency), and cross-asset EOD data (futures, equities, ETFs).
• Experience building or scaling data pipelines, ETL processes, and data-quality frameworks using tools such as Snowflake, SQL, Pandas, NumPy, and workflow schedulers (e.g. Airflow).
• Ability to operate as a senior technical voice, setting standards, influencing architectural choices, and driving high-quality engineering practices.
• Strong communication skills, able to work closely with researchers, engineers, and trading teams on complex data problems.
• Commercial mindset with a focus on accuracy, reliability, and timely delivery in a trading-adjacent environment.
• Experience with multiple regions or exchanges (US, Asia, Europe) is advantageous.

Benefits and Incentives

• Competitive total compensation package with performance-linked bonus.
• Hybrid working model and a collaborative culture that values impact, autonomy, and continuous improvement.
• Growth opportunity to lead technical direction on a core strategic initiative in a high-performing systematic team.
• Exposure to a wide range of datasets, trading desks, and cutting-edge research tooling.

If you’re an experienced data scientist or data-focused engineer with a strong grasp of market data, production-quality Python, and statistical time series work and you want to help define the data backbone of a systematic trading group, I’d love to hear from you.

Apply now or get in touch for a confidential discussion.