Quant Developer / Researcher (London)

Salary: £65,000 - 105,000 per year

Requirements:

• We typically expect three to seven years of professional experience in quantitative development, research engineering, or a closely related technical role, with at least some experience in or alongside financial markets.
• We require exceptional programming ability, particularly in Python, with a record of writing clean, modular, tested, production-quality code and experience with profiling and performance optimisation.
• We look for a very good understanding of AI pipelines, including LLM-based systems, agentic orchestration, retrieval and context engineering, and evaluation and testing of non-deterministic components.
• We expect proven experience taking research or prototype code into production and maintaining it thereafter.
• We require sufficient proficiency in R to understand and faithfully translate existing research code into Python.
• We look for a good understanding of capital markets, including instruments, market structure, and related data.
• We expect some exposure to quantitative research concepts such as return forecasting, factor models, backtesting, portfolio construction, or statistical inference on financial data.
• We require fluency with modern engineering practices, including version control, automated testing, continuous integration, code review, and reproducible environments.
• We seek a clear and credible ambition to move into a research role, supported by curiosity and analytical rigour.
• We value strong collaboration and communication skills in a research-driven environment.
• We look for deep familiarity with the Python numerical and data stack, including NumPy, pandas, SciPy, scikit-learn, and modern columnar tooling such as Polars or DuckDB.
• We value hands-on experience with agent frameworks, LLM APIs, and evaluation harnesses for LLM-based systems.
• We value experience with performance optimisation, parallelisation, or distributed computing.
• We value experience working with large financial datasets, including point-in-time data, vendor feeds, and corporate action handling.
• We value prior experience migrating a research codebase between languages, particularly from R to Python.
• We welcome a postgraduate qualification in a quantitative discipline or comparable evidence of self-directed research capability.
• We look for people who set a high technical bar, take pride in the quality of their work, and think logically and systematically.
• We value intellectual ambition, initiative, ownership, healthy scepticism, and the ability to work collaboratively while maintaining high standards for speed and quality.

Responsibilities:

• Scale research code from prototypes to robust, production-grade implementations, prioritising correctness, speed, memory use, and reproducibility.
• Design, build, and maintain agentic AI research pipelines, including orchestration, tool use, context management, evaluation harnesses, and guardrails.
• Automate research, data, and reporting workflows end to end to reduce manual steps and operational risk.
• Convert existing R research code to Python while preserving numerical equivalence and improving structure, testing, and maintainability.
• Put research models, backtesting frameworks, and analytics into production, and develop the Python research infrastructure used by the team.
• Apply sound engineering practices to infrastructure, including version control, monitoring, data quality controls, testing, code review, and environment management.
• Evaluate emerging AI models, frameworks, and evaluation methods for their suitability in our research stack.
• Work with senior researchers to construct and test return-forecasting signals, from initial specification through empirical evaluation.
• Run in-sample, out-of-sample, robustness, and sensitivity checks, and report research results honestly, including limitations and weak results.
• Build diagnostics and evaluation frameworks that make research results easier to examine and challenge.
• Assess potential data sources for coverage, quality, point-in-time integrity, and economic rationale before they enter the research process.
• Document methodology, results, and limitations to the standards of a regulated investment process.
• Progressively take ownership of research questions end to end, including economic rationale, hypothesis formation, data engineering, factor construction, and testing.

Technologies:

• Agentic AI
• AI
• LLM
• Python
• Quant
• numpy
• pandas

More:

We are Lazard, one of the worlds preeminent financial advisory and asset management firms, with a global presence and a close, collaborative community of just over 3,000 professionals. Our culture supports knowledge sharing, skill development, relationship building, and the growth of creative ideas and individual perspectives. Through Lazard Asset Management, we help clients invest for the future, including retirement, intergenerational wealth, and organizations working toward a smarter, healthier, and more sustainable world. We are seeking a Quant Developer / Researcher to join our Quantitative Research team in London. This development role begins with an approximately even split between quantitative development and research, with a planned shift toward research as the successful candidate builds expertise and contributes to a track record of research. We are committed to attracting, developing, and retaining talent from a wide range of backgrounds and perspectives, and to supporting every colleagues professional growth and contribution to our shared success. This is a full-time position.

last updated 39 week of 2026