Research Engineer, Portfolio Management Group (PMG Tech), Associate

Develop and maintain data pipelines, web-harvesting processes, and scalable data solutions supporting portfolio risk and quantitative analysis.

Collaborate with risk managers, quantitative analysts, AI leads, and engineers to convert business risk workflows into actionable insights and data products.

Build research tools, dashboards, and AI-assisted capabilities using Python, SQL, cloud data platforms, and workflow orchestration to support decision-making.

Strong programming skills in Python and SQL with experience in data engineering or analytics for data-intensive applications.

Bachelor's or master's degree in computer science, data science, data engineering, or related fields.

Experience with web-harvesting, cloud data platforms (e.g., Snowflake, BigQuery, Google Cloud), and AI/ML tooling including large language models.

Work Experience Required: Not explicitly mentioned in the JD.

Experienced in building data solutions that integrate investment research and risk management workflows.

Comfortable working in cross-functional teams combining engineering, research, and business stakeholders with ability to translate requirements into scalable technical products.

Familiar with AI-assisted research applications and advanced data workflows using cloud infrastructure and orchestration frameworks.