Responsibilities

• Candidates must be willing to participate in at least one in-person interview, which may include a live whiteboarding or technical assessment session.
• This role addresses the complex challenge of understanding and optimizing the customer lifecycle through rigorous data-driven analysis and insights.
• The successful candidate tackles key business problems surrounding customer retention, lifetime value, and engagement by building robust analytics frameworks and predictive models.
• Translates massive datasets into actionable recommendations that directly influence retention strategies.
• Bridging the gap between raw data and business stakeholders, this role drives the long-term scalability of reporting systems and supports collaborative AI initiatives across the enterprise.
• Lead end-to-end analytical projects, translating complex business problems into actionable customer lifecycle strategies and data-driven recommendations
• Design, develop, and maintain robust reporting suites and interactive dashboards that provide clear visibility into customer lifetime value, engagement, and churn metrics
• Conduct advanced statistical analysis to identify key business drivers of customer retention and establish measurable key performance indicators (KPIs) that align with department OKRs
• Collaborate with Data Science teams to prepare high-quality datasets, engineer features, and translate AI model outputs into intuitive business recommendations
• Leverage generative AI and analytics automation tools to streamline reporting workflows, write efficient SQL queries, and accelerate data exploration
• Mentor junior analysts by providing technical guidance, conducting peer code reviews, and documenting analytical processes to ensure long-term scalability