Quantitative Data Analyst

Lazard is one of the world’s preeminent financial advisory and asset management firms. Our people and culture make the difference . While global in presence and reach, ours is a close, collaborative community of just over 3,000 professionals. Lazard is a place of continuous knowledge sharing, skill development and relationship building, where professionals grow and succeed together. Our entrepreneurial culture, flat structure and embrace of individual differences, allow creative ideas, original concepts, and unique perspectives to drive our business forward — and for careers to take flight. The Advantage Quantitative Equity team is hiring a Quantitative Data Analyst to take ownership of the quality, reliability, and usability of the quantitative datasets that power our research and production investment workflows. These datasets are the direct inputs to factor models, risk models, alpha signals, backtests, and live portfolio construction - data quality here has real investment consequences. We'll trust you to: 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, known quirks, and intended use in research and production workflows 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 dashboards - implemented in code, not spreadsheets Investigate data anomalies impacting research or production output: triage, isolate root cause, quantify impact, coordinate remediation, and write the code that prevents recurrence Write Python scripts, pipelines, and utilities (using pandas, NumPy, and related libraries) to automate validation, onboarding, reconciliation, and monitoring workflows; collaborate with quant developers to harden and operationalize your solutions Maintain high-quality dataset documentation and operational runbooks (definitions, assumptions, known quirks, troubleshooting guidance), improving consistency and conventions across the data ecosystem Maintain datasets over time through routine checks, backfills, and improvements as vendor definitions, schemas, and business requirements evolve Engage constructively with internal teams and external vendors when addressing data issues or evaluating new sources You’ll need to have: Bachelor’s degree in a quantitative discipline (e.g., Statistics, Mathematics, Economics, Finance, Computer Science) or equivalent practical experience Hands-on experience working with quantitative financial datasets - e.g., prices/returns, fundamentals, corporate actions, security master / reference data, factor data, risk model inputs - from vendors such as Bloomberg, Refinitiv/LSEG, Compustat, FactSet, or ICE Solid understanding of common time-series data quality challenges in a systematic investment context: staleness, point-in-time correctness, survivorship bias, partial trading days, identifier changes (CUSIP/ISIN/ticker), and corporate action adjustments 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, pipelines, and reusable utilities independently; comfortable with pandas, NumPy, file I/O, and scheduling 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 It’s a bonus to have: Experience at a quantitative asset manager, systematic hedge fund, or similar investment data environment 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 What we offer: We strive to enhance the total health and well-being of our employees through comprehensive, competitive benefits. Our goal is to offer a highly individualized employee experience that enables you to balance your commitments to career, family, and community. When you work for Lazard, you are working for an organization that care about your unique talents and passions, and will continue to invest in the development of your career. We expect the base salary range for this role to be approximately $90,000 - $150,000 USD. Various factors contribute to determining the actual base compensation offered, including but not limited to the applicant’s years of relevant experience, career tenure, qualifications, level of education attained, certifications or other professional licenses held, and relevant skills for the role. Base salary is one component of Lazard’s compensation package, which also includes comprehensive benefits and may include incentive compensation. Does this sound like you? Apply! We’ll get in touch and let you know the next steps. Representation at Lazard Lazard is an intellectual capital business committed to delivering the best advice and solutions to clients. To achieve these objectives, we focus on attracting, developing and retaining the best talent. We believe that a workforce comprised of people who represent a wide array of backgrounds, experiences and perspectives creates a rich variety of thought that empowers us to challenge conventional wisdom, solve problems creatively and make better decisions. Lazard was built on the premise that a multicultural firm can best serve a global clientele. As a global firm that has grown organically from local roots in different countries, we have a deep tradition of respecting and appreciating individual differences. Doing so has been core to our success for over 175 years. We are committed to sustaining an environment where every colleague is supported in their professional pursuits, can maximize their individual potential and contribute to our collective success.