Overview

Senior Python Risk Quantitative Analyst Jobs in City Of London, UK at Barclay Simpson

Location: City Of London

Senior Python Model Developer – Market / Credit Risk

Barclay Simpson is partnering with a leading FTSE-listed financial services firm to hire a Senior Python Risk Quantitative Analyst into its London-based Financial Risk team.

This is a high‑impact opportunity within a visible, technically strong function responsible for the firm’s market, credit, capital and liquidity risk models. The role offers direct exposure to senior stakeholders and genuine ownership of model development.

What you’ll be doing

  • Designing and enhancing Market Risk models (VaR, Expected Shortfall, stress testing)
  • Contributing to Credit Risk model development (wholesale / traded exposure preferred)
  • Rebuilding and optimising existing quantitative models
  • Developing and deploying production‑quality Python code
  • Supporting automation and model lifecycle improvements

    Working closely with Validation, Regulatory Capital, Finance and Technology teams

  • Contributing to ongoing cloud migration (GCP environment)

What we’re looking for

  • Strong Python (Pandas, Num Py; production‑level code)
  • Solid experience developing financial risk models within:
    • Strong understanding of:
      • Commercial mindset – able to balance modelling rigour with delivery pace
      • Confident communicator, comfortable engaging non‑technical stakeholders

      The Environment

      • Strong interaction with senior leadership
      • Modern tech stack (Python, SQL, Git‑based deployment, cloud transition underway)

      Location:

      London

      If you’re looking for a role with genuine ownership and breadth — rather than a siloed “factory” environment — this could be an excellent next step.

      Message Scott Nye at Barclay Simpson for a confidential discussion.

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      Title: Senior Python Risk Quantitative Analyst

      Company: Barclay Simpson

      Location: City Of London, UK

      Category:

       

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