• Develop a deep understanding of customer journey phases and key business metrics • Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments • Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights • Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes • Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends • Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets • Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments • Translate complex concepts into implications for the business via excellent communication skills, both verbal and written • Understand what matters most and prioritize ruthlessly • Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

• Develop a deep understanding of customer journey phases and key business metrics • Perform analytical deep-dives to analyze problems and opportunities, identify the hypothesis and design & execute experiments • Inform future experimentation design and roadmaps by performing exploratory analysis to understand user engagement behavior and derive insights • Create personalized segmentation strategies leveraging propensity models to enable targeting of offers and experiences based on user attributes • Identify key trends and build automated reporting & executive-facing dashboards to track the progress of acquisition, monetization, and engagement trends • Extract actionable insights through analyzing large, complex, multi-dimensional customer behavior data sets • Monitor and analyze a high volume of experiments designed to optimize the product for user experience and revenue & promote best practices for multivariate experiments • Translate complex concepts into implications for the business via excellent communication skills, both verbal and written • Understand what matters most and prioritize ruthlessly • Work with cross-functional teams (including Data Science, Marketing, Product, Engineering, Design, User Research, and senior executives) to rapidly execute and iterate

• Apply statistical and econometric modeling, time series analysis, optimization methods, and generative AI to develop improved approaches to demand modeling, elasticity estimation, price recommendation, competition analytics, and related challenges. • Develop reusable tools, frameworks, and components to support and accelerate delivery of value from data science. • Deploy scalable and maintainable solutions to cloud environments, leveraging version control practices and robust code quality and documentation standards. • Work independently and as part of the Data Science Research team, contributing to research prioritisation and technical direction in collaboration with the Director and Product leadership. • Demonstrate technical excellence by delivering high-quality, innovative solutions and championing best practices to ensure research outputs are reproducible, scalable, and maintainable. • Contribute to evaluation and adoption of appropriate tools, programming languages, and technologies. • Mentor junior team members, sharing knowledge and supporting their professional development. • Identify and contribute to patent opportunities and the company's intellectual property portfolio. • Collaborate across Development, Product, Analytics, and Commercial teams to ensure solutions address business challenges and stakeholder objectives. • Partner with operational teams to ensure data pipelines and infrastructure are robust, secure, and optimized for research and production workloads. • Communicate technical concepts and outcomes effectively to both technical and non-technical audiences. • Stay current with developments in data science, machine learning, and AI, applying state-of-the-art techniques to project work. • Develop comprehensive knowledge of the retail fuel industry to understand domain challenges and help guide product innovation. • Share knowledge and promote best practices across the team and company.

• Design, build, and maintain pricing and risk models for a wide range of P&C insurance products • Apply machine learning and AI algorithms to enhance pricing accuracy and risk segmentation • Lead forecasting initiatives and align insights with broader strategic and financial planning • Evaluate Wakam’s aggregate risk exposure to identify potential risk accumulation and ensure alignment with internal limits and reinsurance treaties • Track and analyze exposure levels across portfolios, focusing on sum insured, policy limits, and risk accumulation across geographical areas, product lines, and coverages • Automate and optimise the model development lifecycle • Ensure regulatory compliance and contribute to model governance best practices • Mentor junior team members and foster a high-performance analytics culture