Quantitative Data Engineer

• 1+ year experience (or exceptional new-grad) with Python, SQL, and a cloud data stack; strong CS/engineering/quant fundamentals.
• Evidence of outstanding quality - top academics, competitions, publications, or high-impact projects.
• Either CFA Level I passed or enrolled OR PhD / Master’s in a quantitative field (see qualifying disciplines below).
• Genuine interest in asset management and financial markets.

Advanced Quantitative Education - What Qualifies

A PhD or Master’s degree in a quantitative field is a strong asset. Qualifying disciplines include:

Field cluster

Example degrees

Why it matters

Financial Engineering / Quant Finance

MFE, MSc Financial Engineering, PhD Mathematical Finance

Fluency in portfolio theory, risk, derivatives, performance

Applied Mathematics & Statistics

MSc/PhD Statistics, Applied Math, Actuarial Science

Risk modelling, factor analysis, time-series methods

Computer Science / Data Science / ML

MSc/PhD CS, Machine Learning, Data Science

Core to data engineering and agentic AI

Econometrics / Quant Economics

MSc/PhD Econometrics, Quantitative Economics

Market data, forecasting, analytics

Physics / Engineering (quant-heavy)

PhD Physics, Computational Eng., Operations Research

Advanced modelling, optimization, numerical methods

Who You Are

An ambitious, high-caliber early-career professional who wants to grow fast in a collaborative team and become a CFA-credentialed data engineer.

Pulled from the full job description

• 401(k)
• Vision insurance
• Dental insurance
• Life insurance, * 401(k)
• Dental insurance
• Life insurance
• Vision insurance