VP - Platform Engineer

My client, a leading investment bank, is looking for a VP level platfform enigneer to work within their leading quant trading team, with strong programing skills and command of CI/CD pipelines. This role sits at the core of front‑office quantitative engineering, building high‑performance models, analytics, and computational tooling that directly influence trading decisions across complex markets. You'll architect advanced modelling frameworks, deploy scalable analytics engines, and engineer deep‑data systems that extract alpha from market microstructure and evolving risk landscapes.

Working hands‑on with traders, quants, and technologists, you'll shape the mathematical and computational backbone that powers pricing, strategy optimisation, and real‑time risk intelligence.

The ideal candidate blends mathematical depth with engineering precision and thrives where milliseconds, reliability, and model correctness matter. You bring strong skills in algorithms, simulation, time‑series modelling, and computational optimisation, paired with the ability to communicate complex ideas clearly. You can challenge assumptions, design scalable systems under pressure, and translate market intuition into high‑impact analytical tools. A passion for building robust, elegant, production‑ready quant systems defines your mindset.

• Engineer and optimise quantitative models for pricing, risk, and strategy development, converting advanced mathematical formulations into high‑performance production code.
• Conduct sophisticated statistical research and large‑scale data modelling to extract predictive signals from multi‑asset market behaviour.
• Partner closely with trading and structuring teams to build bespoke analytics, scenario engines, and workflow‑critical decision tools.
• Maintain and enhance front‑office analytical libraries with a focus on computational efficiency, robustness, and seamless integration with real‑time systems.
• Drive innovation by introducing new modelling methods, numerical algorithms, and emerging computational techniques relevant to modern trading.

• Strong proficiency in Python or C++ with experience building production‑ready, low‑latency quantitative tools.
• Deep understanding of quantitative finance, including stochastic processes, derivatives pricing, statistical modelling, and numerical optimisation techniques.
• Solid engineering practices including version control, automated testing, CI/CD pipelines, and modern software development workflows.
• Ability to decompose complex market, pricing, or risk problems into elegant algorithmic and mathematical solutions.
• Excellent communication skills with experience collaborating directly with traders, quants, and engineering teams in fast‑paced environments.