Director - Customer Lifetime Value & Analytics - eCommerce/D2C - IIM/ISB/XLRI

Description:

Location: Gurgaon/Bengaluru

Experience: 8-12 years

About the Role:

The Director of CLV & Analytics will be responsible for defining and driving our customer retention and monetization strategy.

This role is crucial for maximizing the long-term value of our customer base by leveraging advanced analytics, predictive modeling, and deep customer segmentation.

You will lead a team of data scientists and analysts, translating complex data insights into actionable business strategies for marketing, product, and operations.

Key Responsibilities:

- CLV Strategy: Develop and execute the comprehensive strategy for improving Customer Lifetime Value (CLV), including identifying key drivers, predicting churn, and defining personalized customer journeys.

- Advanced Analytics: Lead the development of predictive models (e.g., propensity to buy, churn models) and sophisticated segmentation to target customers with the right product/offer at the right time.

- Data Infrastructure: Partner with the Tech and Data Engineering teams to ensure the necessary data infrastructure and tools are in place to support real-time CLV measurement and strategic initiatives.

- Cross-Functional Collaboration: Act as the strategic partner to Marketing, Product, and Finance teams to drive initiatives like loyalty programs, subscription model optimization, and promotional effectiveness based on ROI and CLV impact.

- Reporting & Insights: Establish key CLV metrics, dashboards, and reporting mechanisms for executive leadership, providing clear, concise, and actionable recommendations.

Desired Candidate Profile:

Education:

MBA from a premier institute (IIM/ISB/XLRI, etc.) or a Master's degree in a quantitative field (Statistics, Economics, Computer Science).

Experience: 8-12 years in Analytics, Consulting, or Business Intelligence, with a minimum of 4 years focusing specifically on CLV, Retention, and/or Segmentation in a high-volume E-commerce, D2C, or SaaS company.

Skills:

- Expert proficiency in SQL, Python/R, and data visualization tools (Tableau/Power BI).

- Strong understanding of statistical modeling and machine learning techniques.

- Exceptional leadership and storytelling ability with data