Senior Quantitative Data Analyst/Engineer at Lazard in London

Job description

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. Many of the world’s leading investors — from individuals to institutions across the globe — have entrusted Lazard Asset Management. We pride ourselves in uncovering the best investment opportunities for our clients. The purpose of our asset management business is to help our clients invest for the future — whether it’s for retirement, to grow and preserve inter-generational wealth, or to benefit the organizations that make our world smarter, healthier and more sustainable. Role Profile: Lazard Asset Management's Advantage Quantitative Equity team is hiring a Senior 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. This is a hands-on, senior role. You will take over our existing datasets, some of which need care and attention, and make sure they are in standard, consistent forms. You will extend and improve our history (longer coverage, higher frequency) and expand the data we have. You will also build the automated validation, monitoring, and investigation tooling that keeps our data reliable. The goal is a durable suite of programmatic solutions that lets you and the rest of the team detect, diagnose, and resolve issues quickly. The role combines data analysis and data engineering. You will be a data specialist who can also model datasets, design and improve tables and schemas, work directly with our databases, and build the pipelines that load and maintain them. You will join our London team and work closely with our team in the Boston and New York offices. The team is small and the work is consequential, with short feedback loops and close collaboration with our quantitative researchers and portfolio managers. This role requires substantial hands-on experience with quantitative financial data in an investment setting - vendor feeds, time-series datasets, and the data quality problems specific to systematic investing. Candidates without that background are unlikely to be a fit. We'll trust you to: O wn quant datasets (market data, fundamentals, corporate actions, identifiers/reference data) end to end: their structure, lineage, known quirks, and intended use in research and production. It is on you to make sure the data is fit for use and that data projects keep moving. Assess the current state of our datasets, prioritise remediation, and make incremental improvements to existing tables and databases, including restructuring them where needed. Model and design datasets: choose the right grain, keys, and history handling (e.g. slowly changing reference data vs. daily time series, point-in-time / as-known storage), and implement those designs in our databases. Extend and enrich datasets: longer history, higher frequency (e.g. monthly to daily), additional coverage. Onboard new datasets end to end: profiling, schema/coverage validation, identifier mapping and normalisation, cross-source reconciliation, documentation, and support for productionisation. Build and maintain automated data validation and monitoring (completeness, timeliness, duplication, outliers, stale/missing series, mapping breaks), with clear quality metrics and dashboards -