Data Analyst

●       Data Extraction & Manipulation: Utilize advanced tools (SQL, Python, R) to extract, clean, and manipulate large, complex datasets from multiple internal and external sources (e.g., ERP systems, point-of-sale data, market syndication).

●       Business Intelligence & Reporting: Design, develop, and maintain dynamic BI dashboards (e.g., Power BI, Tableau, otc) to track daily, weekly, and monthly category KPIs (sales, margin, inventory turns, market share).

●       Performance Analysis: Conduct deep-dive analyses into category performance, assessing the ROI of promotional campaigns, pricing elasticity, and product assortment efficiency.

●       Market & Shopper Insights: Monitor consumer trends, competitor activities, and market dynamics to provide proactive recommendations to the Category Management team.

●       Cross-Functional Collaboration: Partner closely with Category Managers, Supply Chain, and Marketing teams to translate complex data findings into strategic, easy-to-understand business narratives.

●       Predictive Modelling: Assist in forecasting category trends, demand planning, and identifying seasonal shifts using statistical and predictive modelling techniques.

●       strong analytical abilities to interpret market trends and sales data,

●       excellent negotiation skills to manage supplier relationships and contracts effectively, and strategic thinking to develop and execute category plans aligned with business objectives.

Additionally, communication skills are crucial for collaborating with internal teams and stakeholders, and proficiency in project management ensures efficient execution of category initiatives and optimizations.