Mayank Gupta

• • Developed an AI based Competitor Media Intelligence tool using OpenAI APIs to identify advertised brands from display banners on competitor e-commerce websites, enabling new brand acquisition opportunities for Carrefour's Retail Media sales team. Also, leveraged OCR (Tesseract) for text extraction and CLIP-based multimodal embeddings, and Approximate Nearest Neighbor (ANN) search using FAISS, to accurately match banner creatives with a large catalog of brand embeddings.

• • Built end-to-end data products leveraging Carrefour's customer, online & Intore transactions, and media data to create insights used by brands for targeting & converting customers, and campaign planning.

• • Leveraged customer segment models based on ML & Statistical models like RF, Gradient Boost, clustering to identify customer ethnicities, cross-sell opportunities, LTV , promo-sensitive personas, Lifestage-based segments.

• • Architected campaign measurement frameworks and automated Python/SQL pipelines to compute uplift, incremental ROAS, and attribution across stores and customer segments, reducing manual effort by 80% significantly improving speed, unlocking new revenue opportunities.

• • Partnered with engineering teams to build scalable data pipelines and dashboards, ensuring high data quality, reliability, and real-time availability for revenue-impacting decisions.

• • Developed and Deployed Advanced Customer Segmentation models: Leveraged ML techniques like Random Forest and XGBoost to build models that predicted key customer attributes like Ethnicity, Promo-sensitivity, Lifestage, Affluence, Mission, CLV and Cross-sell models. Successfully implemented these models into production.

• • Achieved AED ~80M Incremental Revenue per year: Leveraged customer models and segmentations across multiple tactical and targeted campaigns for 5+ GCC markets to generate substantial incremental revenue.

• • Accurately Evaluated Campaigns: Implemented robust methodologies to accurately assess the impact of My Club days, Target Plans, and Tactical campaigns, providing critical insights for future campaign strategies.

• • Delivered Comprehensive Sales Decomposition, Country Deep Dive and Mall Footfall Analysis: Provided actionable insights for C-suite executives, identifying key drivers of YoY sales change.

• • Built Power BI Dashboards to showcase key customer metrics and perform deep-dive sales analyses, empowering business to take informed decisions.

• • Implemented Amazon's AI based DeepAR algorithm for Demand Forecasting in AWS Sagemaker improving accuracy by 10% saving AED 2M.

• • Identified optimal product Pricing by calculating price elasticities using Logarithmic Regression & Random Forest.

• • Optimized Working Capital through product range reduction. Executed the project for 5 different business units

reducing the inventory by AED 8M within 4 months.

• • Optimized trade marketing spend by 14%, eliminating least effective tactics across channels, geographies & product groups through detailed exploratory analysis, hence saving AED 2.4M.