Data Scientist, Enterprise Data Technology

Responsibilities: Partner with users to understand research workflows, data dependencies, and quality requirements Own datasets and data products end to end: discovery, onboarding, validation, documentation, support, and enhancement Analyze source data for coverage, timeliness, consistency, outliers, and quality risks Design and build automated data quality checks, monitoring, alerting, and reporting Evaluate new vendor datasets for suitability in investment research workflows Collaborate with data engineers, data managers, and platform teams to deliver production datasets Communicate with external data providers to define integration requirements Act as product owner for data domains, prioritizing improvements based on impact and risk

Key requirements: Experience in data science, data engineering, analytics, or related quantitative field Strong Python and SQL skills; experience with large, complex datasets Familiarity with financial instruments, reference data, market-data vendors, and investment research workflows Ability to investigate data issues, build quality systems, and communicate findings clearly Ability to work independently on ambiguous problems while collaborating with stakeholders Strong written and verbal communication skills and attention to detail communication attention to detail cross-functional collaboration Python SQL data quality