University of Illinois, Urbana-Champaign

Aug 2022 - May 2023

Master of Science in Business Analytics

International Institute of Information Technology, Bengaluru

Mar 2020 - Apr 2021

Post Graduate Diploma in Data Science with Specialization in Deep Learning

VIT University (Vellore Institute of Technology)

Jun 2015 - May 2019

Bachelor of Technology in Computer Science and Engineering

Gies College of Business

Aug 2023 - Dec 2023

Graduate Teaching Assistant

• Deployed an end-to-end LLMs based chatbot (OpenAI, LangChain), using ChromaDB, AWS (Kendra, Textract, DynamoDB) and presented insights with robust graphs, thereby reducing the end BI documentation time by 6 hours weekly
• Designed the Business Practicum course, partnered with clients to establish project scope, facilitated student-client collaboration, and offered ongoing technical and conceptual mentorship throughout the term

Wolters Kluwer

Jan 2023 - May 2023

Analytics Consultant

• Leveraged advanced topic modeling techniques such as Latent Dirichlet Allocation (LDA) and guided LDA to effectively analyze copious amounts of ticketing data from multiple global regions
• Employed unsupervised machine learning algorithms to accurately classify tickets into their respective issue categories, streamlining the issue resolution process for faster turnaround times

UIUC Athletics

Aug 2022 - Dec 2022

Data Analyst

• Trained natural language processing machine learning models using Python to automate incident ticket routing
• Explained summer project and results to VP-level organization (20+ colleagues) during end-of-internship presentation

Electronics Corporation of India (ECIL)

May 2017 - Jun 2017

Data Science Intern

• Developed predictive maintenance models by analyzing real-time sensor data from electronic systems, increasing equipment uptime by 15% and reducing maintenance costs by 20% annually.
• Optimized inventory management using machine learning algorithms to forecast demand for electronic components, achieving a 25% reduction in stockouts and improving supply chain efficiency.

TIFAC-CORE(VIT)

Jan 2017 - Apr 2017

Student Intern

• Acquired hands-on knowledge of implementing the Internet of Things (IoT) using sensors and cloud platforms to enable intelligent systems, with practical exposure to real-world applications.
• Gained skills in integrating various sensors and leveraging cloud computing frameworks to process and analyze data for innovative solutions in automotive infotronics and smart technologies.

UnitedHealth Group

Jul 2023 - Present

Data Scientist (ML & AI Innovations)

• Leveraged OpenAI GPT for call transcription analysis & Azure Document Intelligence, LLMs for text extraction on health benefits data, enhancing client interactions and provider-patient alignment with business insights.
• Spearheaded ML initiatives using ensemble models on EHR, claims data, increasing claims approval speed by 34%.
• Deployed end-to-end fraud detection frameworks using Azure Data Factory, Python, and ML models (SVMs, DBSCAN, RF, GBM) to identify irregular claim patterns, categorize risks, and reduce fraudulent claims.
• Developed ETL pipelines using Amazon EMR, SQL, SSIS, reducing processing time & ensuring data accuracy.
• Implemented supervised learning (Decision Trees) & unsupervised learning models on AWS SageMaker for customer segmentation, to facilitate recommendations & improve policy renewal rates by 28%.

Seagate Technology

Sep 2021 - Jul 2022

Data Scientist

• Leveraged AWS Kinesis, Isolation Forests, Autoencoders, computer vision techniques (YOLO, OpenCV, CNNs) for fault detection in HDD platters, improving anomaly detection & reducing false positives.
• Implemented predictive models using time-series forecasting (LSTMs, ARIMA), classification techniques (Random Forest, XGBoost), GCP, and BigQuery to predict equipment failures, reducing downtime by 30%.
• Utilized ETL scripts, AWS Glue for data extraction & transformation of 50M+ records, enabling ad hoc querying.

Ganit Inc.

Mar 2020 - Aug 2021

Sr. Data Science Analyst

• Developed churn prediction frameworks using K-Means Clustering, RFM Analysis, Random Forest, XGBoost, AWS SageMaker, reducing churn by 26% while increasing customer retention and customer lifetime value.
• Boosted ROI by 30% leveraging collaborative filtering, rule-based algorithms, PySpark, Azure Databricks, Apache Kafka to deliver personalized discounts and recommendations through marketing strategies.
• Optimized cross-selling and up-selling strategies using price elasticity models, Market Basket Analysis, and Reinforcement Learning, enhancing purchase frequency and driving revenue growth with product bundling.
• Conducted sentiment analysis using AWS Athena, NLP techniques (BERT, TF-IDF, Word2Vec, Naive Bayes) on 210K+ reviews to extract critical insights, refine feedback loops, and enhance customer satisfaction.
• Implemented time-series analysis, regression-based (DTs, XGBoost), deep learning models, Amazon Forecast to forecast inventory demand across 15K+ SKUs over 20+ distribution centers, reducing stockouts by 32%.

Boston Consulting Group (BCG X)

Jul 2019 - Feb 2020

Data Science Analyst

• Developed Tableau and Power BI dashboards to track KPIs and STAR metrics for data-driven decision-making.
• Implemented a scalable architecture in Snowflake, integrating with AWS S3 & GCP to centralize analytics.
• Conducted A/B tests and causal inference, increasing customer engagement and conversion rates by 29%.
• Collaborated with 12+ cross-functional teams for efficient project management and client satisfaction.