Machine Learning Quant

Anson McCade
28 Jul 2017
15 Aug 2017
Contract Type

Machine Learning Quant

London based

The primary aim of this team is to research and develop quantitative models for the Equity Derivatives business, as well as to ensure their compliance with internal policies and industry regulations.

The Equity Derivative Analytics team's mandate is to use cutting edge data analysis techniques such as Machine Learning to optimize business processes and decisions across the Equities business. The team will work closely with many business stakeholders such as Trading, Sales, Structuring, and Technology to formalize and specify problems and deliver solutions end-to-end.


  • Developing models for pricing and risk management of Flow and Exotic equity derivatives.
  • Providing day-to-day support for the trading desk: discussing new ideas, analysing complex problems and providing solutions.
  • Implementing new models / products in our quant library and writing model documentation.
  • Working closely with technology teams for model testing and deployment in production.
  • Interacting regularly with model governance and risk/valuation control teams.

Essential attributes
• Familiarity with application of Machine Learning techniques in either an academic or industrial context; experience in application of these techniques to finance is a plus.
• Knowledgeable in leading edge technologies and commercial sources of "Big Data". Exceptional software design and development skills across a range of programming languages. Knowledge of ML libraries such as sklearn / TensorFlow.
• Excellent verbal and written communication skills; able to effectively communicate complex algorithmic concepts in investment terms to non-quants.
• Self-motivated, detail-oriented and proactive; able to take ownership of projects from start to finish. Ability to project a vision and push/sponsor/advertise solutions internally.
• Excellent analytical and problem-solving abilities.
• Outstanding academic record with a higher degree in a mathematical subject from a top-tier institution.
• Good written and oral communication.
• Thorough understanding of equity derivatives pricing theory and standard models.
• Strong coding skills: C++/Python development experience.
• Experience in a front-office derivatives trading environment.