• Owning and leading the end-to-end data strategy for the S/4HANA programme • Defining and driving data governance, data quality frameworks and the migration roadmap • Partnering with business process owners on critical data objects and domains • Overseeing cleansing, mapping, transformation and validation activities across systems • Managing relationships with System Integrators and data migration partners • Tracking progress, mitigating risks and ensuring cutover readiness • Acting as the data authority within the programme, influencing decisions and priorities

• Lead the design, execution, and interpretation of A/B tests and quasi-experiments to evaluate the impact of user migration initiatives (PS4 to PS5), growth marketing strategies, and campaign performance. • Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles. • Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results communication. • Apply advanced causal inference methods when experimentation isn’t feasible or to inform test design and prioritization. • Help define and contribute to centralized experimentation frameworks, tools, and documentation to scale best practices across the company. • Independently extract, transform, and analyze data from complex systems using SQL, Python, and other analytics tools. • Communicate findings clearly to technical and non-technical stakeholders, helping drive business decisions with rigor and clarity. • Stay current on new methodologies in experimentation and causal analysis, and bring fresh perspectives to the team’s work.

• Design, execute, and interpret A/B tests and quasi-experiments, and apply advanced causal inference methods when experimentation isn’t feasible. • Partner with cross-functional teams (product, engineering, marketing) to embed experimentation into development and iteration cycles and communicate results with the company’s senior leadership. • Mentor and guide other Data Scientists, providing thought leadership and technical direction. • Serve as a thought leader on best practices for hypothesis development, metric selection, test structure, and results communication. • Help define and contribute to centralized experimentation frameworks, tools, and documentation to scale best practices across the company. • Independently extract, transform, and analyze data from complex systems using SQL, Python, and other analytics tools. • Communicate findings clearly to technical and non-technical stakeholders, helping drive business decisions with rigor and clarity. • Stay current on new methodologies in experimentation and causal analysis, and bring fresh perspectives to the team’s work.

• Lead advanced analytics initiatives: Design experiments, develop statistical and machine learning models, and leverage AI to uncover trends, anomalies, and drivers of performance. • Take ambiguous business challenges and structure them into data-driven solutions. • Transform insights into action: Create clear narratives and recommendations supported by hypothesis testing and statistical analysis. • Communicate effectively: Present methodologies, insights, and recommendations to technical and non-technical audiences through compelling visualizations and storytelling. • Collaborate cross-functionally: Partner with data engineers, analysts, and business stakeholders to deliver end-to-end analytics solutions, dashboards, and reports using SQL, Python, R, and other tools. • Innovate and mentor: Contribute to the growth of Allstate’s Data Science practice by researching new tools, sharing best practices, and mentoring team members.