Data Analyst – Quantitative Research

About the role

Lazard’s Quantitative Equity team is seeking a Data Analyst to own the quality, reliability, and usability of the quantitative datasets that power research and production investment workflows. You will become the domain expert for key data sources, ensuring they are clean, well‑documented, and ready for analytical use.

Key responsibilities

• Act as domain owner for core quant datasets (market data, fundamentals, corporate actions, reference data) and understand their structure, lineage, and analytical purpose.
• Onboard new datasets end‑to‑end, including profiling, schema validation, identifier mapping, cross‑source reconciliation, documentation, and production support.
• Build and maintain automated data validation and monitoring processes (completeness, timeliness, duplication, outliers, stale series, mapping breaks) with clear quality metrics.
• Maintain datasets over time through routine checks, backfills, and improvements as vendor definitions and business requirements evolve.
• Investigate data issues impacting research or production, isolate root causes, quantify impact, coordinate remediation, and help prevent recurrence.
• Write Python scripts, pipelines, and utilities to automate validation, onboarding, reconciliation, and monitoring workflows; collaborate with quant developers to operationalize solutions.
• Maintain high‑quality dataset documentation and operational runbooks, improving consistency across the data ecosystem.
• Engage constructively with internal teams and external vendors when addressing data issues or evaluating new sources.

Required profile

• Bachelor’s degree in a quantitative discipline (e.g., Statistics, Mathematics, Economics, Finance, Computer Science) or equivalent practical experience.
• Strong familiarity with quantitative/financial investment datasets such as prices, fundamentals, corporate actions, security master, macro or alternative data.
• Experience working with vendor datasets, reconciling across sources, and managing schema or definition changes over time.

Required skills

• Python programming for data automation and pipeline development.