Quantitative Data Scientist

Your mission is to

• Partner closely with quantitative researchers to identify, evaluate, and acquire new datasets relevant to trading and market research initiatives.
• Design, build, and maintain reliable Python-based data pipelines for collecting, cleaning, transforming, and storing research data.
• Develop automated workflows and processes to support systematic trading research and strategy development.
• Create analytical frameworks and tooling to process large datasets and generate statistical insights.
• Build and maintain research databases, data models, and data quality monitoring processes.
• Perform exploratory data analysis and statistical investigations to support alpha generation and hypothesis testing.
• Collaborate with researchers to operationalize research methodologies into repeatable analytical workflows.
• Manage data infrastructure running on cloud or dedicated server environments, ensuring stability, reliability, and performance.
• Document data sources, pipeline architecture, methodologies, and analytical processes to support knowledge sharing and reproducibility.
• Stay current on emerging data sources, technologies, and quantitative research techniques relevant to financial markets and options trading.

It could be a match if you have

• Circa 1-3 years of experience in data engineering, data science, quantitative research support, or a related technical role.
• Strong Python programming skills with the ability to write clean, maintainable, and efficient code.
• Experience building and maintaining automated data pipelines.
• Strong understanding of probability, statistics, and quantitative analysis.
• Solid mathematical foundation, including multivariable calculus, linear algebra, and statistical inference.
• Experience working with large datasets and relational databases.
• Demonstrated ability to translate research requirements into technical solutions.
• Experience working in Linux/server-based environments.

Desirable

• Experience in financial markets, trading, or quantitative investing.
• Familiarity with options markets, derivatives, and volatility products.
• Experience supporting systematic trading or quantitative research teams.
• Knowledge of cloud infrastructure (AWS, GCP, Azure).
• Experience with time-series analysis and financial data.
• Exposure to machine learning techniques and predictive modeling.
• Experience working with alternative data sources.