FRM (Fraud Risk Monitoring)  using unsupervised Anomaly detection models based on customer’s past expenditure, current credits, customer profile and other essential features.

▪ Real-time prediction of engagement disposition based on the agents remarks in delinquency management system to increase the operational efficiency.▪Compute the contactability score of customer based on engagements performed by both Telecaller and FOS agents for collection▪ Designed DW and Data pipelines.▪ Completed Sentimental Analysis on the message received via Chatbot.

▪ Saved 2.8 MN USD by predicting new clinical sequelae after Long Covid to 8 MN people using PASC Risk Calculator. ▪ Minimised revenue leakages by saving 1.2 MN USD: Identified challenges in Sleep Apnea treatments which are due to non-compliance and procedural challenges using a data model which led to a saving of 1.2 MN USD annually. ▪ Infection Surveillance Platform: Predicted the trajectory of an infection and identified when a normal infection turns into an outbreak from 70 million health claims in 3yrs ▪ Worked on Patenting and publishing the new ML models and the research contribution in building disease prediction and forecasting models. ▪ Automated the retraining pipeline of the Deployed models and continuously monitoring the accuracy of deployed models using ML Ops. ▪ Awarded Excellence Award in 2021 for innovative solutioning and implementation of PASC Risk Calculator.

▪ Conceptualized, Designed and built Fraud detection AI/ML product integrated with Loyalty program to detect and prevent fraudulent transaction, solution to increasing liability in Raymond and achieved Liability reduction of Rs. 95Lakh in 120 outlets ▪ Breakthrough Recommendation engine: Increased the average basket size of the customers by recommending up-selling and cross-selling opportunities of products resulting in 10% increase in the over-all sales of Himalaya ▪ Solution architect and project manager: Re-designed omnichannel scalable Loyalty platform and Offer engine for Raymonds, Biba and Himalaya. ▪ Frequency builder model - In Biba, this model predicted customers' next purchase date to implement an effective campaign strategy resulting in an increase of overall customer frequency of 8% and sales by 7%. ▪ Set up a team of data scientists, machine learning engineers and big data specialists to carry out data analysis, research & build AI/ML product. ▪ Implemented effective Digital campaign for sharp focused customer segment based on ML clustering techniques with significant sales increase. ▪ Analyse the requirement and strategize approach for analysis of data set using regression policies ▪ Awarded star achiever award for FY 2018-2019 and Most Valuable player for FY 2017-18 for outstanding performance.

▪ Turned around loss making Rights out deals into profitable through setting the optimum Royalty and Guarantees values predicted by ML Models ▪ Performed Exploratory Data Analysis - Data collection, pre-processing, hypothesis testing, data transformation, outlier detection and treatment. ▪ Fine-tuned the deployed models and continuously monitored the accuracy of deployed models. ▪ Developed Finance Module of the Rights Logic product using MVC Framework, .Net 4.5, Rest Web API and Oracle 11g. ▪ Visited Clients like Major League Baseball, USA and National Basketball Association, USA for business meetings to gather business requirements, understand their workflows and facilitating Smooth UAT and Production deployments.

Developed Analytical Dashboard and MIS Reports| Royal Mail, UK ▪ Developed Descriptive Analysis dashboard using Tableau. ▪ Developed MIS report using data warehouse and SQL.

Product development and Optimised Reports| Royal Mail, UK ▪ Developed reporting module with complex reports in an existing product ADC (Automated Data capture) ▪ Optimised existing reports by identifying heavy and re-writing SQL queries to significantly improve the system’s performance.