Head of Analytics Engineering

Overview

As Head of Analytics Engineering, you will lead the strategy, design, and delivery of analytics products across Cross Asset, Fund, Private Markets, and Predictive Analytics. You’ll own end-to-end engineering of scalable, production-grade analytics capabilities, including AI/ML-driven insights, aligned with client workflows. You’ll combine domain expertise in fixed income and derivatives with large-scale distributed systems leadership to drive architecture, governance, and lifecycle management. You will partner with Product, Research, and Commercial leadership to shape a differentiated, data-driven offering and scale a high-performing analytics engineering organization.

Pay / Benefits

• healthcare
• retirement planning
• paid volunteering days
• wellbeing initiatives

Responsibilities

• Define and execute the Analytics Engineering strategy for a portfolio of analytics products, aligned to the Data and Analytics Product Engineering unit
• Translate customer and market needs into scalable analytics capabilities and roadmaps, including AI/ML components
• Contribute to engineering direction and market positioning as a leader in analytics and data-driven capabilities
• Lead architecture, design and delivery of production-grade analytics products across real-time and batch use cases
• Set and enforce engineering best practices (code quality, testing, observability)
• Own delivery of complex, high-impact programs with cross-team alignment
• Provide strategic technical leadership, guiding architecture and critical design decisions
• Drive integration of AI/ML into analytics products with production readiness, monitoring, and governance
• Evaluate and adopt emerging technologies to enhance capabilities and commercial value
• Apply deep domain expertise in fixed income and derivatives to ensure analytics outputs are accurate and workflow-aligned
• Partner with Sales, Product, Research, Data Platforms, Communities and adjacent Engineering teams to scale outcomes
• Build trusted relationships across LSEG and align priorities to strategy and customer outcomes
• Influence without authority to unify teams around common goals and optimize tradeoffs
• Translate complex technical concepts into clear business insights and decisions
• Lead and scale a high-performing analytics engineering organization with an inclusive culture
• Ensure alignment and collaboration across teams, programs, and senior stakeholders

Key requirements

• Master’s degree in computer science or computer engineering with deep expertise in scaling analytics computations for financial markets
• Strong domain knowledge in fixed income and derivatives, including pricing and risk concepts
• Strong programming expertise (Python, Java, C++) with experience building distributed data and analytics systems
• Strong understanding of AI/ML systems and production deployment, including model lifecycle management
• Experience within a financial data provider, exchange, sell-side institution, or quantitative firm with a comparable data and analytics ecosystem

• collaborative leadership
• stakeholder management
• strategic thinking
• Python
• Java
• C++

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