Quantitative Data Scientist in New York, New York at Kpler

The Quantitative Data Scientist will serve as a critical bridge between research and technology, enabling the firm's systematic trading and options research initiatives through robust data acquisition, engineering, and analytics capabilities.

This role is responsible for sourcing and integrating new datasets, building and maintaining reliable research data pipelines, developing analytical processes to transform raw data into actionable insights, and supporting quantitative researchers with scalable tools and infrastructure. The ideal candidate combines strong software engineering skills with a solid mathematical and statistical foundation and is comfortable working hands-on with large financial datasets.

• 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.