Executive Director, AI & Quant Analytics

Create your best future as an Executive Director, AI and Quant Analytics!

What's the role?

The Executive Director, AI and Quant Analytics plays a key role in shaping, applying and interpreting quantitative models and analytics that support pricing, risk, portfolio and strategic decision making across Commodities, Trade and Transition (CTT). This role is for an experienced quantitative analyst who combines strong analytical depth, market understanding and commercial judgement, working closely with trading, risk and quantitative engineering partners to ensure analytics are economically sound, explainable, and decision relevant. The role focuses on model insight, analytical leadership and business partnership, rather than core platform or software engineering ownership. This role focuses on analytics that inform real pricing, risk and portfolio decisions, engaging directly with stakeholders helping shape real outcomes.

Key Responsibilities include:

• Quantitative Analysis & Modelling:Lead analytical investigations into model behaviour, sensitivities, limitations and economic realism.
• Analytics, Insight & Decision Support: Translate complex quantitative outputs into clear insights, recommendations and trade-offs for Markets and Risk stakeholders.
• Model Governance & Control:Take accountability for model documentation, assumptions, validation evidence and ongoing performance assessment.
• Markets Partnership & Thought Leadership:Provide guidance and mentoring to junior analysts, uplifting analytical standards across the team.

What do I need?

This role suits a commercially minded quantitative professional with a strong academic foundation and handson experience applying analytical models in financial services. You'll bring the ability to balance technical rigour with practical decisionmaking, and to communicate complex ideas clearly to a broad range of stakeholders.

Additional experience and skills include:

• Strong grounding in applied quantitative techniques, including statistics, probability and optimisation
• Experience applying pricing, risk or portfolio models within banking or financial markets environments
• Proficiency in Python or R for quantitative analysis and modelling
• The ability to explain complex analytical and quantitative concepts clearly to nontechnical audiences
• Sound judgement in balancing analytical depth with realworld commercial needs
• It is desirable to have exposure to commodities, trade finance, derivatives or structured products
• Strong SQL capability and experience working with large, complex datasets is ideal
• Familiarity with model validation, model risk or governance frameworks would be advantageous
• Exposure to machine learning or advanced analytics in applied environments
• Experience collaborating closely with quantitative or software engineering teams

• Strong engineering capability in Python, with proficiency in at least one of C++, Java or C#
• Advanced SQL skills and confidence working with largescale, dataintensive workloads
• Solid grounding in applied mathematics, statistics, probability or optimisation
• Proven experience building scalable, productiongrade analytics systems
• Background in quantitative development, analytics engineering, or frontoffice analytics within financial services
• It is desirable for you to have experience with cloud platforms, preferably Azure and modern CI/CD practices
• You will ideally have exposure to machine learning tooling (such as PyTorch or TensorFlow) and LLM frameworks