Applied AI ML Director, Risk Management & Compliance

Overview

In this leadership role, you guide AI-driven risk solutions within Risk Management & Compliance to strengthen resilience and responsible growth. You shape and pilot transformative AI initiatives, including Gen AI, across Market, Country, and Principal risks, collaborating with product, engineering, and business teams. You’ll lead a high-performing data science group, delivering robust AI tools and scalable analytics in a cloud-enabled, enterprise environment. You’ll oversee model risk governance, explainability, and production monitoring, ensuring real business value and seamless integration into operations. This role offers strategic influence, hands-on technical work, and opportunities to.

Responsibilities

• Oversee and manage a team of data scientists developing predictive models, prompt-based LLM solutions, autonomous agents and agentic systems
• Lead design, build, and deployment of AI and data-driven applications with Product, Business and Engineering teams
• Utilize cloud, data mesh, and knowledge base tech (repositories, semantic search, automated retrieval) to organize data and insights
• Distill complex analyses for senior leadership to inform strategy
• Manage end-to-end model development lifecycle including risk management and alignment with business objectives
• Adhere to model risk management, responsible AI, governance, explainability and compliance
• Collaborate with senior leaders to re-engineer processes and embed AI into workflows
• Integrate data science solutions into operational workflows to drive value and adoption
• Guide research and pilot projects to apply state-of-the-art AI/ML, including GenAI and agentic tech
• Implement drift monitoring and model retraining to maintain accuracy and performance

Key requirements

• Extensive experience in data science or analytics
• Proven track record deploying and operating AI/ML models in large-scale enterprises, including ML Ops, monitoring, and lifecycle management
• Strong leadership experience in managing data science/R&D teams
• Experience with AI/ML algorithms, statistical modeling, scalable data processing, Databricks or equivalent, cloud technologies, data mesh, and big data ecosystems
• Experience with A/B testing, data-driven product development, and cloud-native deployment in distributed environments
• Excellent written and verbal communication for technical and business audiences
• Scientific mindset with ability to work independently and in teams
• Ability to collaborate across a matrix organization and multiple locations
• Hands-on experience with agentic frameworks and orchestration (e.g., LangGraph, Google ADK)

• strong communication
• leadership
• collaboration
• AI/ML algorithms
• ML Ops
• databricks or equivalent

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