Quant Developer / Researcher (London)

Quantitative Research (Growing Over Time)

We'll trust you to:

• Work with senior researchers to construct and test return-forecasting signals, from initial specification through empirical evaluation — running in-sample, out-of-sample, robustness, and sensitivity checks, and reporting results honestly, including where they are weak.
• Build diagnostics and evaluation frameworks that make research results easier to interrogate and challenge.
• Vet candidate data sources for coverage, quality, point-in-time integrity, and economic rationale before they enter the research process, and document methodology, results, and limitations to the standard expected of a regulated investment process.
• Over time, take ownership of research questions end-to-end: economic rationale, hypothesis formation, data engineering, factor construction, and testing.

You'll need to have:

• Typically three to seven years of professional experience in quantitative development, research engineering, or a closely related technical role, at least part of it in or alongside a financial markets environment.
• Exceptional programming ability. Python to a very high standard, with a demonstrated record of clean, modular, tested, production-quality code, and comfort with profiling and performance optimisation.
• A very good understanding of AI pipelines: LLM-based systems, agentic orchestration, retrieval and context engineering, and the evaluation and testing of non-deterministic components.
• Proven experience taking research or prototype code into production and owning it thereafter.
• Sufficient proficiency in R to read, understand, and faithfully translate existing research code into Python.
• A good understanding of capital markets — instruments, market structure, and the data that describes them.
• Some exposure to quantitative research concepts such as return forecasting, factor models, backtesting, portfolio construction, or statistical inference on financial data.
• Fluency with modern engineering practice, including version control, automated testing, continuous integration, code review, and reproducible environments.
• A clear and credible ambition to move into a research role, supported by evidence of curiosity and analytical rigour.
• Strong collaboration and communication skills in a research-driven environment.
• Deep familiarity with the Python numerical and data stack (NumPy, pandas, SciPy, scikit-learn, and modern columnar tooling such as Polars or DuckDB).
• Hands-on experience with agent frameworks, LLM APIs, and the design of evaluation harnesses for LLM-based systems.
• Experience with performance optimisation, parallelisation, or distributed computing.
• Experience working with large financial datasets, including point-in-time data, vendor feeds, and corporate action handling.
• Prior experience migrating a research codebase between languages, particularly R to Python.
• A postgraduate qualification in a quantitative discipline, or comparable evidence of self-directed research capability.

Personal Characteristics

• Sets an exceptionally high technical bar and takes evident pride in the quality of what is built.
• A logical, structured thinker who reasons from first principles and writes code that reflects that clarity.
• Genuine intellectual ambition — wants to understand and eventually own the investment ideas, not only implement them.
• Strong sense of initiative and ownership; drives projects forward at pace with appropriate guidance from senior team members.
• Healthy scepticism, particularly towards AI-generated output and results that look too good to be true.
• Operates effectively in a collaborative, research-oriented environment while holding a high personal bar for speed and quality.

#LI-HB1 #LAM

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.