Data Analyst, Quantitative Research

Lazard Ltd; Boston (MA); On-site; USD 90,000 - 150,000; Full time

Benefits offered by this job

Comprehensive benefits

Individualized employee experience

Job summary

Lazard Ltd is hiring a Data Analyst in Boston, MA, who will manage the quality and usability of quantitative datasets central to research and investment workflows. The successful candidate will onboard new datasets and build rigorous validation processes using SQL and Python.

This role requires a Bachelor's degree in a quantitative field and strong analytical skills. The position is hybrid, allowing for flexible work arrangements.

Qualifications

• Bachelor’s degree in a Quantitative Discipline (e.g. Statistics, Mathematics) or equivalent practical experience.
• Strong familiarity with quantitative/financial datasets, including prices, returns, and fundamentals.
• Experience working with vendor datasets and reconciling across sources.

Responsibilities

• Become a domain owner for key quant datasets and develop a deep understanding of their structure.
• Onboard new datasets end-to-end including profiling, validation, and documentation.
• Build and maintain automated data validation processes for completeness and timeliness.

Skills

SQL

Python

Data Analysis

Collaboration

Data Validation

Education

Bachelor’s degree in a Quantitative Discipline

Tools

Snowflake

Docker

Kubernetes

Job description

The Advantage Quantitative Equity team is hiring a Data Analyst to take ownership of the quality, reliability, and usability of the quantitative datasets that power our research and production investment workflows. The core of this role is to become deeply familiar with our data, how it is sourced, shaped, validated, monitored, and used, then build automated solutions that keep it clean and reliable at scale.

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, 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

You’ll need to have:

• 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: write clean, maintainable scripts and pipelines independently. Comfort with pandas/NumPy, file I/O, scheduling, and building reusable utilities
• Strong analytical and debugging mindset; 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)

It’s a bonus to have:

• 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

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 cares 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.

Job Info

• Job Identification 6148
• Degree Level Bachelor's Degree
• Locations 222 Berkeley Street, Boston, MA, 02116, US 30 Rockefeller Plaza, New York, NY, 10112, US (Hybrid)