About Me

I'm someone who gets genuinely excited about solving puzzles, especially the kind that involve millions of data points and real-world impact. My journey started at IIT Madras, where I discovered that I love the challenge of taking complex problems and breaking them down into elegant solutions. That's what led me to Columbia for my Master's in Data Science, and now I'm putting those skills to work at CVS Health.

What I'm most proud of isn't just the technical achievements, it's the human side of the work. I recently led a project that completely transformed how we process business data, and the most rewarding part wasn't the coding or the algorithms. It was sitting down with stakeholders from different teams, understanding their pain points, and building something that actually made their lives easier. That project now generates $3M annually and earned me a Premier Award, but what I remember most is the look on people's faces when they realized how much time we'd saved them.

I've always been drawn to the intersection of technology and people. At Columbia, I taught Data Visualization to 120+ graduate students, and I loved seeing that moment when complex concepts clicked for someone. I've published research papers, won hackathons (including first place at Harvard's LISH competition), and built systems that process everything from healthcare claims to credit recovery models. But what keeps me motivated is knowing that behind every algorithm, there are real people whose work gets easier because of what we build.

These days, I'm particularly fascinated by generative AI and large language models. There's something incredible about teaching machines to understand human language and generate code that actually works. I believe the future of data science isn't just about building better models, it's about making AI more accessible and practical for everyone who needs it.

5+

Years Experience

50+

Projects Completed

10+ Millions

in Cost Savings

Professional Experience

Data Scientist

CVS Health 2023 - Present
  • Saved $9.6M by optimizing overpayment detection algorithms in healthcare claims
  • Built a 0→1 data pipeline combining structured and unstructured data; added $3M/year and won Excellence Award
  • Used LLMs and GenAI to auto-generate SQL/Python from healthcare docs, reducing SME involvement

Data Analyst

DIA Ventures 2023
  • Engineered a hybrid ML framework combining regression and classification to estimate credit recovery
  • Built clustering models to segment credit card audiences across partner ecosystems

Capstone Project

Columbia University 2022
  • Boosted recommendation precision by ~30% using semantic search and NLP
  • Designed a two-stage recommendation architecture leveraging content-based filtering and real-time ranking for hyper-personalized results
  • Integrated clickstream trends into pipelines via Dataiku for seasonal model tuning

Data Science Intern

Novelis Inc. 2022
  • Deployed computer vision pipelines to track and measure product dimensions in real-time using live plant video streams
  • Automated CI/CD on Databricks using GitHub Actions; saved 12–16 hours/week
  • Cut Spark query runtimes by 84% through optimization and profiling

Teaching Assistant

Columbia University 2022
  • Led recitations and office hours for 120+ graduate students in Data Visualization
  • Collaborated with faculty to refine curriculum for analytical communication and social science data interpretation

Undergraduate Researcher

IIT Madras 2020 - 2021
  • Simulated optical properties of nanoparticles using novel approximation algorithm; RMSE ranged from 0.01–0.06
  • Published research in Materialia exploring plasmonic nanoparticle behavior in solar energy devices
  • Mentored a six-member team on modeling techniques and scientific publishing

Machine Learning Intern

University of Michigan 2020
  • Achieved R² = 0.96 using convolutional neural networks (CNNs) for material property prediction from atomic structure features
  • Executed 1800+ ab initio energy simulations across 10 alloy families to curate a robust training dataset

Undergraduate Researcher

IIT Madras 2019 - 2020
  • Trained a Random Forest Classifier with tuned hyperparameters to reach 86% accuracy on microscopy image-based predictions
  • First-authored a peer-reviewed paper in Computational Materials Science on data-driven sintering behavior prediction

Awards & Recognition

Premier Award

CVS Health

Recognized for leading the technical development for a claims prioritization model that streamlined audits and drove $3M in annual medical cost savings

B.Krishnamurthy Award

IIT Madras

Best Bachelors Thesis in Metallurgical and Materials Engineering

Vijay Jagannathan Award

IIT Madras

Award for the best academic performance in graduating batch for Metallurgical and Materials Engineering curriculum

Skills & Technologies

Programming Languages

Python SQL R C++ MATLAB

Machine Learning & AI

Generative AI Large Language Models Scikit-learn Recommendation Systems TensorFlow NLP

Big Data & Cloud

Google Cloud Platform Spark SQL Hadoop

Analytics & Visualization

Matplotlib Seaborn Plotly Dash

Healthcare Analytics

Insurance Data Claims Analysis Payment Analytics Predictive Analytics

Tools & Platforms

Git Jupyter Azure Databricks Dataiku

Get In Touch

Let's Connect

I'm always open to new opportunities and interesting conversations about data science, AI, and healthcare technology.

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