Translate large, complex datasets into actionable business insights using analytics, data visualization and statistical modelling.
Apply descriptive, diagnostic, and predictive analytics, including regression and other statistical models, to explain business performance and forecast outcomes.
Design, analyze, and interpret A/B tests and experiments, ensuring statistical rigor and business relevance.
Identify and analyse e-commerce trends related to category and supply chain.
Partner with category teams, data engineering, data science teams, and external developers to deliver scalable analytical solutions.
Act as a trusted analytics advisor to business stakeholders, influencing strategy through data.
Develop repeatable, automated, and scalable frameworks for ongoing analysis and reporting.
Ensure data quality, consistency, and governance across pricing data, dashboards, and reports.
Present insights, recommendations, and trade-offs to senior leadership with clear storytelling and visualizations.
Scope and structure new analytical initiatives that drive incremental business value.

5+ years of experience in data analysis, business analytics, or data science roles, preferably in B2C e-commerce or retail.
Strong business, finance, and economics foundation with the ability to connect data to commercial outcomes.
Proven experience with statistical analysis, regression models, and predictive modeling.
Hands-on experience designing and analyzing A/B tests or experiments.
Advanced proficiency in SQL and Excel.
Experience with BI and visualization tools (e.g., Power BI, Tableau).
Working knowledge of Python and/or R for data analysis and modeling.
Excellent communication and storytelling skills, including executive-level presentations.
Strong project ownership and prioritization skills in fast-paced environments.
Master’s degree or higher in a quantitative field (preferred).

A high-impact role in a global, data-driven organization.
Collaboration with diverse, international teams.
Continuous learning opportunities.
Competitive compensation and benefits.
Access to inclusive employee networks (Women, Pride, Young Employees, Disability).
Time and support for corporate volunteering and community impact.

Senior Data Scientist, E Commerce

Key skills