Key Responsibilities
Customer Intelligence & Data Foundation
- Define and manage roadmap for data foundation, customer profiling & segmentation and modelling based on business priorities to support CRM, marketing, commercial, and general business strategies.
- Develop customer analytics solutions, including predictive models, propensity scores, behavioural segments, and other inferred customer attributes.
- Establish standard operating procedures, documentation, and collaborate with data analysts and IT team to operationalize analytical models.
- Regularly review and enhance segmentation logic, model assumptions, variables, and thresholds to improve accuracy, relevance, and business impact.
Business Analysis & Strategic Insights
- Lead analysis to address business questions, deliver business insights and strategic recommendations for decision-makers.
- Measure impact of strategic initiatives, campaigns related to customer behaviours and recommend opportunities for optimization.
- Proactively identify new analytical opportunities that can improve customer experience and business performance.
Business Intelligence & Reporting
- Develop and maintain automated dashboards and analytical reports using BI tools to monitor customer segments, segment migration, model performance, and key business measurements.
- Ensure dashboards and reporting pipelines are accurate, reliable, scalable, and easy for business users to interpret.
Data Project Management
- Lead end-to-end delivery of supplier dashboard initiative in collaboration with IT, Commercial, and other relevant departments.
- Define project scope, requirements, milestones, dependencies, risks, and acceptance criteria.
- Support user acceptance testing, implementation, documentation, and post-launch performance reviews.
Collaboration
- Serve as a trusted analytical partner to CRM, Marketing, Commercial, IT, and other business units.
- Present analytical findings and recommendations to senior management and leadership in a clear and compelling manner.
- Promote best practices in analytics, experimentation, data visualization, model governance, and insight communication.
Qualifications & Skills
Required
- 5+ years of experience in data analytics, data science, business intelligence.
- Strong proficiency in SQL and working with large, complex datasets.
- Hands-on experience using Python or R for data preparation, statistical analysis, modelling, and automation.
- Strong project-management and stakeholder-management skills, with experience coordinating cross-functional initiatives.
- Strong written, verbal, and presentation skills, including the ability to explain technical concepts to non-technical and senior audiences.
Preferred
- Experience in retail, consumer businesses, e-commerce, CRM, loyalty programs, or customer lifecycle management.
- Experience working with data warehouses (e.g., PostgreSQL, Redshift).
- Familiarity with ETL/ELT processes, data pipelines, or data modelling.
- Experience operationalizing analytical models or customer segments in a production environment.