Data Scientist, Enterprise Data Technology

What you'll do

• Translate user research workflows and data requirements into scalable data products.
• Own datasets end-to-end from vendor evaluation and onboarding to documentation and support.
• Analyze source data to identify coverage gaps, inconsistencies, outliers, and schema changes.
• Design and build automated data quality checks, monitoring, and reconciliation workflows.
• Evaluate new vendor datasets to determine suitability for investment research.
• Communicate with external data providers to investigate issues and define integration requirements.
• Act as a product owner for data domains by prioritizing improvements based on user impact.

What we're looking for

• Experience in data science, data engineering, analytics, or a related quantitative field.
• Strong Python and SQL skills.
• Experience analyzing large, complex datasets.
• Familiarity with financial instruments, security identifiers, reference data, market-data vendors, and/or investment research workflows.
• Demonstrated ability to investigate data issues, build quality systems, and communicate findings clearly.
• Ability to manage ambiguous problems independently while collaborating with technical and investment stakeholders.
• Strong written and verbal communication skills and exceptional attention to detail.