Global Head of Applied AI & Quantitative Modelling

About CRU: 
CRU International is a leading provider of business intelligence and consulting services in the metals, mining, and fertilizer industries. With over 50 years of experience, we offer valuable insights and analysis that help our clients make informed decisions in an ever-changing global market.

About the role: 
The Global Head of Applied AI & Quantitative Modelling will define CRU’s quantitative AI agenda and turn proprietary data and research into predictive, probabilistic and agentic intelligence products. With global scope and executive visibility, this role leads the journey from research and production deployment to commercial impact and P&L, helping transform how commodity market intelligence is delivered.

Responsibilities

Key Responsibilities:

• Set the quantitative AI agenda: Own the global AI and quantitative modelling roadmap, including time-series forecasting, probabilistic forecasts of fundamentals, forward curves and risk solutions.
• Design and deploy production systems: Build and scale production machine-learning systems, from calibrated probabilistic forecasts to multi-agent workflows providing near-real-time analytics.
• Identify product opportunities: Find and capture high-value opportunities by embedding proprietary price, asset and market data into products and platforms used by global financial institutions and commodity market participants.
• Turn models into market impact: Accelerate new AI products to market, working as a peer with Product, Content, Technology and Commercial leaders.
• Represent CRU externally: Advise institutional clients, regulators and industry bodies on AI adoption in commodities and finance.
• Build and develop the team: Recruit and develop quantitative talent and foster a culture of scientific rigour, intellectual honesty and fast delivery.
• Lead quantitative research and development: Partner with multidisciplinary teams of economists, quants and data scientists to develop econometric frameworks, distribution-fitting methods, probabilistic scoring and price indexation models.
• Scale quantitative data pipelines: Scale cloud-based quantitative pipelines that combine high-frequency market data with historical price and asset-level datasets.
• Establish model-risk standards: Set back testing, validation, governance and audit frameworks that can withstand scrutiny from clients, regulators and benchmark users.

Requirements

Qualifications:

• Ph.D. or M.Sc. in Statistics, Applied Mathematics, Econometrics or a related field.

Skills & Experience:

• 15+ years of experience in quantitative research and data science, including senior leadership roles.
• Strong practical command of time-series and probabilistic modelling, gradient boosting, deep learning, and LLM and agentic architectures.
• Fluency in Python, R, SQL and distributed cloud computing.
• Experience deploying quantitative models and AI systems in production, and building quantitative data pipelines.
• Ability to turn complex, sparse or unstructured market problems into commercial, production-grade products.
• Deep understanding of financial markets and/or commodity supply chains, including forward curves and risk frameworks.
• Experience combining high-frequency market data with historical price and asset-level datasets.
• Knowledge of econometric frameworks, probabilistic methods, model validation and model-risk governance.
• Executive presence and the ability to communicate complex concepts clearly to boards, regulators and enterprise clients.
• Proven ability to build stakeholder confidence, lead high-performing teams and collaborate across multidisciplinary functions.
• Desirable: senior leadership experience at a tier-one bank, asset manager, hedge fund, market infrastructure provider, or commodity pricing and intelligence firm; and experience engaging institutional clients, regulators or industry bodies on AI, quantitative modelling or market intelligence.

Benefits

What We Offer:

• Competitive salary and flexible benefits package.
• Opportunities for professional growth and development as part of a global company.
• A collaborative and supportive work environment.
• The chance to work with industry-leading experts and over a diverse range of topics and projects.