Head of Analytics Engineering

Description

The company wants a Head of Analytics Engineering to lead strategy, design and delivery of analytics products across its Cross Asset, Fund, Private Markets and Predictive Analytics offerings. The role reports to the Data and Analytics Engineering CIO.

You would own end-to-end engineering of analytics capabilities, including pricing, risk, derived metrics and AI/ML-driven predictive analytics. The aim is systems that scale, run reliably in production and fit how clients work.

The role needs financial domain knowledge, large-scale distributed systems engineering and applied AI/ML. You would be accountable for how analytics products are built, put into production and scaled across the company.

AI/ML already powers the predictive analytics work and is spreading into Cross Asset, Fund and Private Markets. You would set up the engineering frameworks for integrating, deploying, monitoring and managing models at scale.

The job blends product thinking with deep technical leadership. You would lead a large engineering organisation, set technical direction and work closely with Product, Research and Commercial leaders.

Responsibilities

• Set and carry out the analytics engineering strategy for a portfolio of analytics products, in line with the Data and Analytics Product Engineering business unit.
• Turn customer and market needs into scalable analytics capabilities, and own a forward roadmap covering analytics computations and AI/ML with Product and Commercial teams.
• Help shape the company's engineering direction and its standing as a leader in analytics and data-driven capabilities.
• Lead architecture, design and delivery of production-grade analytics products such as pricing and risk, for both real-time and batch use.
• Set and enforce standards for code quality, testing and observability.
• Own delivery of complex, high-impact programmes and keep teams aligned.
• Give strategic technical direction, guiding architecture and key design decisions.
• Lead the integration of AI/ML into analytics products, covering the path to production, monitoring and governance.
• Assess and adopt new technologies that improve analytics capabilities and commercial value.
• Apply deep fixed income and derivatives expertise to shape products so that pricing, risk and derived metrics are accurate, performant and fit client workflows.
• Work across Sales, Product, Research, Data Platforms, Communities and adjacent engineering teams, so that outcomes scale beyond one domain.
• Build trusted, high-impact relationships across the company, linking analytics engineering priorities to group strategy and customer outcomes.
• Lead without direct authority: bring teams together around shared goals, settle trade-offs and drive decisions that benefit the whole company.
• Explain complex technical ideas as clear business insight for decision makers.
• Build and grow a high-performing analytics engineering organisation with an inclusive, collaborative culture.
• Keep teams, programmes and senior stakeholders aligned.

Requirements

• A Master's degree in computer science or computer engineering, with deep experience scaling analytics computations for financial markets.
• Strong knowledge of fixed income and derivatives, including pricing and risk concepts.
• Strong programming in Python, Java or C++, with proven experience building distributed data and analytics systems, including high-throughput pipelines and low-latency computation.
• Strong understanding of AI/ML systems and production deployment, including model lifecycle management.
• Experience at a financial data provider, exchange, sell-side institution or quantitative firm with a comparable data and analytics ecosystem.

Conditions

The level is Group Director.

The company is a global financial markets infrastructure and data provider with about 25,000 people across 65 countries.

The company is an equal opportunities employer and does not discriminate on any protected basis, and it will make reasonable accommodation for religious practices and for mental health or physical disability needs.

Benefits

• A range of tailored benefits and support, including healthcare, retirement planning, paid volunteering days and wellbeing initiatives.
• Fundraising and volunteering through the company Foundation, which gives charitable grants to community groups that help people access economic opportunities.
• Work on sustainability with customers who have their own sustainability goals.