Data Analyst

Role Overview The Lead – Data Analyst will be responsible for driving data-led decision-making across key business functions including sales, marketing, supply chain, and operations. This role will focus on building advanced analytical models and scalable data systems to improve business performance across areas such as sales elasticity, promotions effectiveness, demand forecasting, production planning, and customer lifecycle management. The incumbent will play a critical role in transforming data into actionable insights, enabling better planning, forecasting, and growth optimization.

This is a high-impact role with strong cross-functional visibility and influence on revenue, efficiency, and customer outcomes. Key Responsibilities 1. Sales & Pricing Analytics Develop and implement sales elasticity models to optimize pricing strategies Analyze impact of price changes on demand, revenue, and margins Support pricing decisions with data-driven insights 2.

Promotion Effectiveness Tracking Design frameworks for promotion tracking and ROI measurement Evaluate effectiveness of campaigns across channels Recommend optimization strategies for future promotions 3. Demand Forecasting & Planning Build and enhance demand forecasting models using historical and real-time data Collaborate with business teams to improve forecast accuracy Drive data-backed planning for seasonal and growth demand 4. Production & Supply Planning Support production planning through data insights and forecasting inputs Work closely with supply chain to ensure optimal inventory levels Identify risks and inefficiencies in supply-demand alignment 5.

Supply Chain Control Tower (Alerts & Insights) Develop real-time dashboards and alert systems for supply chain monitoring Identify anomalies, delays, and stock issues proactively Enable faster decision-making through actionable alerts 6. Distributor & DMS Analytics Leverage Distributor Management System (DMS) data to track sales, inventory, and coverage Identify distributor-level performance gaps and opportunities Drive improvements in channel efficiency and distribution 7. Customer Analytics & CLTV Modeling Build and refine Customer Lifetime Value (CLTV) models Segment customers based on behaviour and value Support retention, cross-sell, and personalization strategies 8.

Data Infrastructure & Dashboarding Build and maintain dashboards for key business metrics Ensure data accuracy, consistency, and accessibility Automate reporting for business teams 9. Cross-Functional Collaboration Work closely with Sales, Marketing, Supply Chain, and Finance teams Translate business problems into analytical solutions Drive adoption of data-driven decision-making across functions 10. Team Leadership Lead and mentor a team of analysts Provide guidance on analytical frameworks and best practices Build a high-performance analytics team Qualifications and Experience Bachelor’s degree in Engineering, Statistics, Economics, or related field; MBA preferred 6 - 10 years of experience in Data Analytics / Business Analytics Strong experience in FMCG / D2C / Retail preferred Experience working with cross-functional teams Proven track record of building impactful analytical models and driving business outcomes