Description

Our client is looking for an experienced modeling leader to own AI/ML strategy across multiple workstreams within a banking environment — someone equally comfortable in the technical weeds and in front of senior leadership.

What you'll own:

• Lead the end-to-end model lifecycle (build, validate, monitor, document) across a portfolio of ML and quantitative models
• Set the modeling playbook — standards, explainability, bias testing — and keep the team accountable to it
• Be the go-to person when model risk, governance, or regulatory questions come up; work directly with risk/compliance
• Run model review/approval cycles and make sure everything clears internal and regulatory bars
• Turn dense technical results into a story execs can act on
• Scout and vet new AI/ML tools and platforms, then make the case to leadership
• Hire, coach, and grow a team of modelers — build a culture that values rigor without losing speed
• Set the team's analytics roadmap, balancing new builds with keeping the lights on
• Partner closely with data engineering, tech, ops, and business stakeholders

What you bring:

• 9-10+ years building/leading quantitative or AI/ML models, including 3+ years managing a modeling or analytics team within banking Sector.
• Range across modeling types — predictive analytics, NLP, optimization, or AI platform evaluation
• Strong Python skills, plus working knowledge of MLOps tooling and large-scale data platforms
• Solid grasp of model risk management, validation frameworks, and what regulators expect
• Comfortable owning conversations with audit, compliance, and model risk teams
• Strong communicator who can flex between technical and executive audiences
• Master's or PhD in a quantitative field (Stats, CS, Math, Data Science, etc.) preferred
• Open to candidates who've led model governance and team delivery in a regulated banking setting

Key Skills

Education

Any Graduate