- Designed and implemented a cross-sell and product recommendation model for different sales channels in Insurance to predict the propensity of the customers to buy another policy.- Empowered channel leads and sales teams with data-driven narratives to effectively  communicate product benefits and increase sales conversions- Collaborated with different stakeholders for the development of a Proof of Concept for leveraging facial scan technology to assess health vitals. This… Show more - Designed and implemented a cross-sell and product recommendation model for different sales channels in Insurance to predict the propensity of the customers to buy another policy.- Empowered channel leads and sales teams with data-driven narratives to effectively  communicate product benefits and increase sales conversions- Collaborated with different stakeholders for the development of a Proof of Concept for leveraging facial scan technology to assess health vitals. This initiative aimed to streamline the underwriting process (augmented underwriting), leading to expedited decision-making, while also exploring potential avenues for reducing claims through proactive health monitoring.- Helped to drive the adoption of data-driven decision-making across cross-functional business units Show less

Sponsorship Market Mixed Modeling and Spend Optimization (CPG Client):Tools/Technologies Used: Python, Regression, Optimization, ExcelMeasured ROI across various marketing channels and geo-regions to help the business perform better budget planning for their future marketing effortsPerformed EDA to identify patterns in the data to propose better marketing strategies.Developed a spend optimizer to recommend scenarios for higher ROI by using spend and incremental sales data using… Show more Sponsorship Market Mixed Modeling and Spend Optimization (CPG Client):Tools/Technologies Used: Python, Regression, Optimization, ExcelMeasured ROI across various marketing channels and geo-regions to help the business perform better budget planning for their future marketing effortsPerformed EDA to identify patterns in the data to propose better marketing strategies.Developed a spend optimizer to recommend scenarios for higher ROI by using spend and incremental sales data using Gekko optimizer.Portfolio Optimization using Clustering and Propensity modeling (CPG Client):Tools/Technologies Used: Python, Spark, Databricks, Azure Data Lake Storage, Machine Learning, GithubHelped to maximize the sales for the existing SKU recommendations and assortment modules by Portfolio Optimization.Developed a portfolio optimization end to end solution for B2B business to strengthen the business revenue and building data-driven strategies around promo campaigns.Created Delta Tables and a Dashboard in the SQL layer of Databricks to track experiments on orders influenced using Recommendation Engine for proactive measurement of production systems. Show less

Writing technical articles related to Data Science

Revenue Growth Management(RGM) Analytics - (CPG Client)Tools/Technologies Used: Python, Regression, Statistics, ExcelWorked closely with Business team to perform analytics looking to solve strategic business questions giving actionable consumer/customer insights and recommendationsIdentify levers to prioritize in order to accelerate Per Capita Consumption (PCC) growthAnalyzed the impact of Penetration, Frequency, and Intensity on PCC. Utilized key external third-party data… Show more Revenue Growth Management(RGM) Analytics - (CPG Client)Tools/Technologies Used: Python, Regression, Statistics, ExcelWorked closely with Business team to perform analytics looking to solve strategic business questions giving actionable consumer/customer insights and recommendationsIdentify levers to prioritize in order to accelerate Per Capita Consumption (PCC) growthAnalyzed the impact of Penetration, Frequency, and Intensity on PCC. Utilized key external third-party data sources such as Kantar, Nielsen, Atlantia Search, IHS Markit, along with Internal data sources to identify actionable levers for optimizing PFI.ITSM Tool ServiceNow Ticket Analytics (Retail Client)Tools/Technologies Used: Python, Regression, NLP, Java, ServiceNow, Jupyter NotebooksPredictive modeling and text analytics using NLP on Support Tickets (ITSM tool) to identify the frequently occurring issues, patterns, related trends and predicting the resolution time for the tickets using Regression algorithmAnalyzing KPI data related to tickets and team’s performance and updating them into a dashboardGenerating Insights identify high impact applications for problem management and possible automation areasAnalyzed requirements and implemented systems to deliver comprehensive development life cycle solutions using Odata API Successfactors and Java Show less