As a Lead data scientist at Paytm's digital advertising & Travel vertical that offers innovative solutions .Paytm- Travel •Built and led a comprehensive data science team in Paytm Travel, set up data science infrastructure, and built pipelines for feature engineering, training, deployment, and A/B testing frameworks. Designed the ML system for handling 60 million customers.• ML solution to search rank all the relevant buses for the user based on their behaviour. Trained ML algorithm & provided ranking predictions for 25 million customers, encompassing 0.35 million buses. .Performed AB testing & Increased booking conversion by 20%.•Cancellation Protect Flight: A ML Solution that predicts if a user is eligible for cancellation protect insurance while booking the flight & once after the eligibility also predicts the price of the premium amount. Impact : Turned a loss-making vertical to a profitable one (1 million$ per month) Paytm Ads• Designed a model for audience targeting that segments and targets users similar to those who are high-performing within a given advertiser or category, with the aim of improving campaign results and advertiser return on investment (ROI); ML segments demonstrated approximately 60% higher CTR compared to rule-based segments and increased the platform's CTR by 15%.• Identified customer personas and created cohorts based on behaviours observed on the Paytm app and ads; this initiative provided insights into hidden patterns and differentiated between good/average and active/dormant customers both for first-party data and MOA.• Developed a generative AI (GenAI) proof of concept (POC) for revenue uplift by enhancing an ML model with visual creative and advertiser features using GPT-4 text and vision API; the POC saw an up to a 13% performance gain, which led to significant impressions inventory savings and a potential ~5% monthly revenue increase.

Operated as a Data scientist at a company that is recognised as the global leader in Industry 4.0 •Historical Time to Action: Developed a model to predict the time to take predictive maintenance action for machine related issues using inference modelling. Significantly reduce the resource cost saving by 50%.•Batch Analytics: Developed a product for managing & predicting batch production in the FMCG sector which will help in forecast production planning & resource allocation. Successfully deployed the ML system for world leading FMCG company.•Proficy Csense : Developed an Industrial advanced analytics software for SME with No code Features and presented post sales demo for more than 20 global customers. •Maintenance Interval Optimization : Used optimization algorithm to determine the proper predictive maintenance interval to avoid excessive or insufficient maintenance, which also help in reducing cost & risk.

⦿ Build an end-to-end analytical product for steel industry for open casting.⦿ Developed a new algorithm to change the classification threshold of ML models using mixed-integer programming which help us to make models for highly imbalanced datasets.⦿ Developed a failure prediction classification model for steel casting using machine learning models & sucessfullys deployed & setup MLOps system with drift detection features on real-time prediction⦿ Developed a regression model to calculate the convection heat transfer from the steel & using those features build a dynamic threshold model.⦿ Created a object detection model to capture the issues on the blade of the wind turbines. ⦿ Successfully deployed the model with scalable architecture & reduced corrective/reactive maintenance cost by 2 percent of the revenue.⦿ Created CI/CD pipeline with automated performance testing and memory profiling for ML-based algorithms⦿ Created Maintenance Interval optimization: Used optimization algorithm to determine the proper predictive maintenance interval in order to avoid excessive or insufficient maintenance,

⦿ Build an end-to-end analytical product for the US govt to investigate child abuses in the country.⦿ Created an analytical tool for in-depth analysis of location-wise crimes with the unsupervised algorithm.⦿ Created a machine learning model which tried to predict the severity of the case with the past data.⦿ Worked on POC for image captioning for the child portal module.⦿ Created a review system for the Client portal using NLP & deployed the model on the server which helps the team to make the product in a better way for future sprint iterations.⦿ I have worked as a member of the LineSight Data Analytics team of Unisys LineSight products. LineSight is a software for doing intelligence analysis on travelers and air cargo shipment, which reduced asset maintenance costs by 40 percent & mitigated risk.