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About the role
Key responsibilities & impact- Embed data-informed thinking into how delivery decisions are made
- Strengthen the use of statistical inference, experimentation, and evidence-based insights across teams
- Coach and support project, product, and delivery practitioners to adopt meticulous, data-driven approaches
- Coordinate across teams, products, and regions to support impactful execution, with strong emphasis on data-backed prioritisation and decision-making
- Establish and embed data-driven decision-making practices across programmes and delivery teams
- Support the adoption of statistical methods (e.g., hypothesis testing, confidence intervals, causal inference) in business and delivery insights
- Ensure key delivery decisions are supported by robust quantitative evidence and clearly stated assumptions
- Partner with Data, Analytics, and Product teams to improve the quality, accessibility, and usability of data
- Lead Communities of Practice and support practitioners in: Translating data into actionable insights; Structuring problem statements using analytical frameworks; Applying data science techniques to delivery, forecasting, and risk management; Strengthening data-backed storytelling and recommendations
- Apply predictive and diagnostic analytics to identify risks and delivery bottlenecks early
- Use data to move from reactive reporting to forward-looking performance management
- Build trusted relationships by bringing analytical thinking and statistical difficulty to decision-making discussions, influencing interested parties through evidence-based insights
- Drive continuous improvement through measurement frameworks with clear KPIs and statistical validation; Experimentation approaches (A/B testing, pilots, controlled rollouts); Embedding a test-and-learn approach
Requirements
What you’ll need- Strong communication with the ability to influence interested parties using data and evidence
- Critical thinking combined with focus on delivery
- Experience leading work in global, cross-functional environments
- Strong analytical capability, including understanding of statistical methods and data science fundamentals
- Proven track record to translate data into decisions and meaningful outcomes for organization
- Strong problem-solving capability using structured and quantitative approaches
- Ability to build capability, support development, and motivate teams
- Strong understanding of delivery frameworks and governance
- Preferred experience leading enterprise scale programmes
- Experience in environments with established data engineering, analytics, or data science practices
- Direct experience applying, or working closely with statistical modelling, forecasting, and predictive analytics
- Experience working in organisations that value data-informed decision making
- Exposure to data platforms, analytics tools, or advanced business intelligence environments
- Experience mentoring teams to adopt data-led decision-making approaches
Benefits
Comp & perks- open and inclusive culture
- great work-life balance
- tremendous learning and development opportunities
- life and health insurance
- medical care package
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
Statistical InferenceHypothesis TestingCausal InferenceData Science FundamentalsQuantitative AnalysisA/B TestingForecastingRisk ManagementData-Backed StorytellingMeasurement Frameworks
Soft Skills
Strong CommunicationCritical ThinkingProblem-SolvingTeam MotivationInfluencing Skills