Data Analyst Manager

About MetaMorph:

We at MetaMorph, empower startups to scale and innovate by placing people at the centre of their strategy. With a proven track record of supporting over 220 startups, we specialise in aligning talent with organizational needs, enhancing employee skills, and transforming employer brands. Our data-driven insights fuel decision-making and provide comprehensive support for both acquisition and being acquired, ensuring you are covered from every angle—360°.

Key Responsibilities (Strategic & Operational):

Analytics Strategy Execution: Implement the data analytics roadmap for the FMCG business as defined by senior leadership. Identify key business questions and determine what data analysis is needed (sales trends, customer behavior, product performance, etc.) to answer them.

Data Collection & Management: Work with IT and operations to ensure data from all outlets (POS systems, online orders, loyalty programs, etc.) is being captured accurately in a centralized data warehouse or analytics system. Improve data quality and integrity through regular audits and validation. Business Insights & Reporting: Analyze large datasets to extract trends and insights on sales performance, popularity of products, customer demographics, and marketing campaign effectiveness. Develop and maintain dashboards and regular reports for different stakeholders (management, marketing, operations) highlighting key KPIs such as same-store sales growth, average ticket size, customer retention rates, etc.

Performance Optimization: Provide data-driven recommendations to improve business outcomes – for example, insights on optimal store operating hours, inventory forecasts to reduce waste, or personalized promotion strategies to increase customer loyalty. Collaborate with marketing and operations teams to test and implement these recommendations.

Tool Implementation: Support the deployment and use of business intelligence (BI) tools and analytics software. Ensure the team is leveraging the right tools (Excel, Tableau/Power BI, SQL, Python, etc.) for efficient analysis and visualization. Work on automating routine reports for efficiency.

Cross-Functional Projects: Participate in cross-functional initiatives such as new product launches or market expansion studies, contributing analytical inputs. For example, help evaluate potential new store locations by analyzing demographic and sales data, or assess the impact of pricing changes on sales volumes.

Required Skills & Competencies:

Technical Analytics Skills: Strong proficiency in data analysis tools and techniques – including advanced Excel, SQL querying, and at least one analytics or visualization tool (Tableau, Power BI, or similar). Ability to handle large datasets and perform complex analyses.

Analytical Thinking: Excellent problem-solving skills with a knack for identifying patterns and root causes from data. Able to translate ambiguous business problems into structured analytical approaches.

Business Acumen: Good understanding of business operations and metrics, ideally in retail or consumer businesses. Able to connect data findings to real-world business implications (e.g., how footfall and conversion rates affect revenue).

Preferred Background & Domain Expertise:

Industry Experience: Experience in data analytics or business intelligence roles within QSR, retail, e-commerce, or consumer goods companies . Familiarity with analyzing sales data, customer purchase patterns, or supply chain metrics in a multi-unit context is highly beneficial.

Education: Bachelor's or Master's degree in Statistics, Data Science, Computer Science, Business Analytics or related field. An MBA with a focus on analytics or operations can also be useful when paired with strong technical skills.

Project Experience: Hands-on experience implementing analytics projects that had tangible business outcomes (e.g., improved sales through customer segmentation, cost savings through inventory optimization).

Experience in an organization scaling up its analytics function is a plus.

International Exposure: Any experience with analytics for markets outside India (for instance, understanding consumer data trends in the UK or handling datasets from different regions) is a plus, aiding in readiness for international expansion.