• Implementation of a machine learning model for a high-tech retail client, aimed at refining delivery date expectations and bolstering customer satisfaction.• Leveraged advanced data science skills to analyze historical delivery data, identify trends, and develop a model for accurate delivery time predictions.• Achieved a notable reduction in late deliveries, lowering the rate to below 10%, consequently enhancing customer satisfaction and operational efficiency for the retail client.• Led the development of Post-Event Analytics for a prominent CPG brand, harnessing SAP Proposal Data to pinpoint areas of failure and quantify associated business costs.Employed advanced Feature Engineering techniques to meticulously document and analyze data at each stage of the process.• Delivered actionable insights that empowered the client to enhance operational efficiency, decrease failure rates, and optimize resource allocation.

• Leveraged probabilistic and inference modeling to deliver targeted recommendations to supply chain decision-makers, resulting in waste reduction and improved predictions of quantities at risk.• Text analysis of feedback and tickets from cloud storage users using Sentiment analysis, Theme Detection to optimize CapEx and OpEx cost using models like BERT, LDA, and Clustering Rule-based Approach• Managed a team of 3 in the development and implementation of projects and tasks

•Collaboratively contributed to a strategic project initiated by the stakeholders, analyzing and recommending profit optimization strategies between in-house and external products.•Applied diagnostic analytics frameworks to identify pivotal insights and proposed actionable improvements, enhancing overall operational efficiency.•Proficiently communicated complex data insights to decision-makers using Power BI Dashboards, contributing to informed decision-making and measurable improvements

Interned with the Discovery team, contributing to:• Automated generation of tailored causal and predictive insights for Finance and Sales teams, elevating weekly sales strategies• Implemented anomaly detection strategies to promptly identify irregularities and pinpoint their root causes, ensuring operational efficiency.• Establishing a benchmark for ranking margins/thresholds, prioritizing key metrics that demanded immediate attention. • Optimizing code efficiency by transitioning from R to Python, leveraging list comprehensions to replace loops and where statements, resulting in a notable 30% reduction in code execution time• Conducted thorough documentation and delivered presentations showcasing internship achievements

•Developed dynamic and interactive Tableau dashboards for customer presentations in the Finance domain.•Extracted and synthesized data from RBI data sources to assess the efficiency, profitability, asset quality, and overall performance of scheduled commercial banks at both group and individual bank levels.•Evaluated the pre and post-merger financial performance of banks by conducting t-Tests on CAMEL ratios.•Compiled comprehensive reports and presented the findings of the internship work.