Senior Manager, Product Data Science & Analytics in City of Westminster

As a Senior Manager of Product Data Science, you will be a key leadership figure within the Product Data Science organization, responsible for building and scaling a high-performing team of analysts and data scientists embedded within product domains.

Responsibilities

• Lead, develop, and grow a team of product analysts and/or data scientists, ensuring consistently high performance, strong technical standards, and clear ownership of impact.
• Drive effective goal‑setting, planning and execution processes across Product Data Science, bringing leadership and discipline to OKRs, prioritisation and delivery against strategic objectives.
• Set and continuously raise the analytical bar, ensuring robust, actionable, and decision‑oriented outputs.
• Act as a senior technical and strategic leader, reviewing and shaping high‑impact analytical work, experimentation design, and advanced modelling approaches.
• Partner with senior product, engineering, marketing and commercial leaders to define priorities, shape roadmaps and ensure data science is embedded in strategic decision‑making.
• Translate ambiguous business problems into structured analytical and data‑science problems, delivering clear, commercially meaningful recommendations.
• Drive adoption of scalable analytical frameworks, experimentation standards and AI‑enabled tooling to improve efficiency, consistency and speed of decision‑making across teams.
• Champion best practices in experimentation, causal inference, segmentation and customer understanding, ensuring statistical and analytical rigor.
• Build and maintain partnerships with data platform, data engineering and other central data functions.
• Build and evolve the team's capability through hiring, coaching and performance management.
• Identify and remove systemic blockers to high‑quality analytics delivery, improving tooling, processes, ways of working and organisational effectiveness.
• Influence and align cross‑functional stakeholders across multiple product domains, ensuring clarity, prioritisation and strong decision‑making discipline.

Qualifications

• Extensive experience in data science or a similar quantitative role, with a proven track record of supporting and influencing a product organization.
• Technical & modelling expertise: expert level proficiency in Python and SQL; deep, hands‑on experience with statistical modelling, (quasi) experimentation, multi‑arm bandit, and a wide range of machine learning techniques such as regression, classification and clustering.
• Product acumen: Demonstrated ability to define, implement and operationalise crucial product and feature‑level metrics from scratch.
• Strategic influence: Proven track record of driving strategic impact through pro‑active collaboration and ability to lead technical discussions, drive product strategy and communicate complex insights effectively to cross‑functional partners.
• Scaling impact: Experience scaling analytics or data science capabilities, driving impact through the creation of automated processes, self‑service tools or data products.
• Critical thinking: Leader in critical thinking, able to analyse facts, evidence, observations and arguments to form judgments by applying rational, skeptical and unbiased analyses.
• Leadership: Outstanding leadership skills, with experience in mentoring, coaching and developing teams of analysts or data scientists.
• Collaboration & communication: Exceptional collaboration and communication skills, able to engage, influence and inspire cross‑functional partners at all levels.
• Cross‑functional partnership: Proven ability to build strong relationships and drive outcomes across product, engineering, data platform and other central functions, often without direct authority.
• Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics or a related quantitative field.
• Preferred Experience
• Experience working within a high‑scale technology, marketplace, e‑commerce or travel technology organisation.
• Strong technical background in product data science, experimentation or machine learning before moving into leadership roles.
• Experience building and scaling experimentation platforms, measurement frameworks, self‑service capabilities or data products.
• Experience applying AI, large language models, agentic AI or automation technologies to improve analytics productivity and decision‑making effectiveness.
• Experience leading organisational change, improving analytical maturity and raising standards across multiple teams or functions.
• Reputation for raising the standard of thinking, execution and decision‑making in the teams and organisations you join.
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