Lazard is one of the world’s preeminent financial advisory and asset management firms, and they are seeking a Data Analyst for their Advantage Quantitative Equity team. The role involves taking ownership of the quality and usability of quantitative datasets, building automated solutions, and maintaining data integrity for research and production investment workflows.
Become a domain owner for key quant datasets (e.g., market data, fundamentals, corporate actions, identifiers/reference data) and develop a detailed understanding of their structure, lineage, and intended analytical use
Onboard new datasets end-to-end: profiling, schema/coverage validation, identifier mapping, cross-source reconciliation, documentation, and support for productionization
Build and maintain automated data validation and monitoring processes (completeness, timeliness, duplication, outliers, stale/missing series, mapping breaks), along with clear quality metrics and reporting, implemented in code, not spreadsheets
Maintain datasets over time through routine checks, backfills, and improvements as vendor definitions, schemas, and business requirements evolve
Investigate data issues impacting research or production workflows: triage, isolate root cause, 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 harden and operationalize your solutions in production
Maintain high-quality dataset documentation and operational runbooks (definitions, assumptions, known quirks, troubleshooting guidance), improving consistency and conventions across the data ecosystem
Engage constructively with internal teams and external vendors when addressing data issues or evaluating new sources
Qualification
Required
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 (e.g., prices/returns, fundamentals, corporate actions, security master / reference data, macro / alternative data sets)
Experience working with vendor datasets; comfort reconciling across sources and managing schema/definition changes over time
Strong SQL skills: ability to write and optimize queries to validate, reconcile, and investigate issues across large analytical datasets
Strong Python skills: able to write clean, maintainable scripts and pipelines independently. Comfort with pandas/NumPy, file I/O, scheduling, and building reusable utilities
Strong analytical and debugging mindset; able to diagnose data inconsistencies systematically and drive fixes through to completion
Strong communication and collaboration skills; effective in small, close-knit teams with direct stakeholder interaction
Exposure to common time-series pitfalls in financial data (staleness, partial trading days, identifier changes, corporate action adjustments, point-in-time behavior)
Preferred
Experience supporting production data pipelines and incident workflows (monitoring, alerts, runbooks, operational readiness)
Familiarity with modern data warehouses (e.g., Snowflake) and/or analytical engines (e.g., DuckDB/Polars)
Cloud experience, preferably Azure
Familiarity with containers and orchestration (e.g., Docker, Kubernetes) and CI/CD practices
Benefit
Comprehensive, competitive benefits
Comprehensive benefits
May include incentive compensation
Lazard is a financial advisory and asset management firm focused on income strategies, alternative investments, and private equity funds.
