Applied AI & ML Lead – Markets Operations

Overview

In this role, you will lead a team of AI/ML scientists and engineers to design, develop, and scale AI-driven solutions for Market Operations. You’ll partner with AI Engineering and business stakeholders to translate needs into robust, production-grade models and tools. You’ll drive technical direction, ensure governance and deployment best practices, and deliver measurable impact. This is a chance to shape AI-driven transformation in a global financial institution with a collaborative, growth-focused culture.

Responsibilities

• Lead end-to-end development and deployment of advanced ML models to support market operations initiatives
• Partner with AI Engineering to ensure robust architecture and deployment patterns aligned with business needs
• Mentor and guide a team of AI/ML data scientists in an agile environment
• Ensure production-grade AI/ML applications are built, maintained, and optimized
• Establish best practices for architecture, evaluation, monitoring, governance, and deployment
• Champion documentation of methodologies, results, and best practices for knowledge sharing
• Align design and delivery with partnering teams to maintain velocity and prioritization
• Engage stakeholders in an agile manner to develop, demonstrate, and iterate on deliverables
• Collaborate with Operations, Technology, and Transformation teams to solve complex problems using AI/ML

Key requirements

• MSc or PhD in Computer Science, Data Science, Machine Learning, or related field
• Proven experience building and deploying AI applications in large-scale production environments
• Experience with MLOps practices and tools for managing the ML lifecycle
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, scikit-learn)
• Strong data preprocessing, feature engineering, and evaluation techniques
• Experience with large, complex datasets and statistical analysis
• Familiarity with cloud platforms (AWS, Azure, GCP) and containerization tools (Docker, Kubernetes)
• Experience managing data science teams and coaching team members
• Strong problem-solving, independent and leadership capabilities in cross-functional teams
• Strong communication skills for technical and non-technical audiences

• leadership
• clear communication
• collaboration
• Python
• PyTorch
• TensorFlow

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