Abhinav Singh

Led the development and deployment of an ML-based delivery time prediction model to improve OTIF (% of on-time & in-full orders) performance across 12+ markets, raising it from 55% to over 85%. Developed a pricing tool to estimate product-level price elasticity and recommend optimal pricing strategies, using Facebook’s Prophet model. Solution was deployed on AWS EKS using Docker and Airflow.

Studied NPS and OSAT to understand the customer loyalty across 5 brands, deployed NLP to user reviews for sentiment analysis and identified 10 key areas of concern using Clustering and Topic Modelling. Developed a Power BI dashboard for the executive team of the client which facilitated them in identification of the critical deals that are under work, projects coming up for renewal and track the in-year savings made on projects.

Analysed and integrated the data in Python from request creation to invoice payment for a client’s spend platform, strategised better pricing for product and identified resource intensive steps in procurement cycle time. Developed a customer risk model using Supervised ML technique and created VBA automated excel dashboard classifying the 95 high-valued customers at High, Moderate and Low risk categories.