Senior Statistician

About the team you are joining As part of the Information and Data (I D) Division, the Data Governance and Analytics team drives best-in-class data practices across the organization. Our mission is to unify data governance, engineering, and analytics to ensure data is accessible, trustworthy, and actionable. We maximize the value of data investments by enforcing strong governance, delivering high-quality data engineering, and enabling advanced analytics. The team promotes responsible data use, provides accurate insights, manages data security risks, and prioritizes initiatives to ensure timely access to the right information for informed decision-making. What your day would be like Reporting to the Sr Manager Data Services, Governance Quality, you will be responsible for designing and applying rigorous statistical methodologies, leading complex analyses, and ensuring the validity, reliability, and interpretability of analytical results. Working closely with business and technical teams, the Senior Statistician translates complex data into actionable insights, develops and validates statistical models, establishes analytical standards and best practices, and mentor junior analysts and statisticians. The role also plays a key part in governance by ensuring appropriate study design, data quality, methodological transparency, and compliance with regulatory or scientific standards. Identify, select, and apply appropriate statistical methodologies and analytical techniques to interpret complex datasets and support evidence-based decision-making. Develop, validate, and document statistical methodologies, and provide expert guidance on their practical application across analytical initiatives. Compile, analyze, and interpret data to identify trends, variations, anomalies, and emerging patterns. Provide technical guidance and peer review to team members on data interpretation, analytical structure, and presentation of statistical findings. Prepare comprehensive analytical reports and technical documentation for management and cross-functional stakeholders, translating statistical results into clear, actionable insights. Design and apply statistical methods to address industry-specific and domain-specific analytical challenges. Conduct model diagnostics, sensitivity analysis, and validation to assess accuracy, stability, and bias. Design and implement statistically valid data collection and sampling methodologies to support advanced analytical initiatives. Maintain strict data quality, security, and confidentiality controls throughout the data lifecycle.