Vishwanath Guruvayur
I love
About Me
Hello! I'm
Vishwanath Guruvayur,
experienced Data Scientist with a passion to transform complex challenges into scalable AI solutions.
I just finished my Master's in Data Science at the University of Virginia with top academic honors, where I dove deep into multimodal Gen-AI research; basically teaching machines to understand text, images, and audio together to make smarter qualitative comprehensions from educational content.
My fascination with data started unexpectedly during my mechanical engineering studies at BITS Pilani. While tinkering with robotics projects, I was mesmerized seeing how data could make machines "think" and act intelligently in the real world. That spark led me down the data science rabbit hole.
During my time at Piramal, I went from intern to leading their new analytics team, tackling everything from preventing massive inventory losses to figuring out ways to retain their best salespeople. Turns out, the right algorithms can save companies serious money and help them understand their people better.
What Drives Me
I'm fascinated by those "aha!" moments when data reveals something unexpected—like discovering that a company's inventory problems aren't actually about demand forecasting, but about how different teams communicate. I love translating complex algorithms into stories that business leaders can act on, turning statistical noise into clear signals.
When I'm not diving into datasets, you'll catch me exploring the mathematical patterns in Carnatic ragas (there's surprisingly beautiful data in Indian classical music!), strumming my guitar, or building quirky side projects that blend my love for music, gaming, and code.
My latest obsession? - Using AI to analyze musical compositions and understand what makes certain melodies so captivating.
Resume
Professional Experience
Lead Data Scientist
Piramal Critical Care
Jan 2022 - Jun 2024
HO Bethlehem, PA (Worked Remotely from Mumbai, India)
Lead various projects implementing Analytics and Data Science in business processes in areas of Supply Chain, Finance and Sales Operations.
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Inventory Stock Forecasting based on Demand & Expiry
Supply Chain & Finance
Developed an Inventory Utilization Scenario Model to minimize Stock-outs and Financial Write-offs based on recent past sales trends, current warehouse inventory, and future demand forecasting. -
Pharmaceutical Market Share & Growth Analytics
Sales Operations & Finance
Conducted in-depth analysis on the Global Injectable Pain & Anesthetics Market and created a tool with visualization dashboards to recommend the best market and portfolio expansions based on advanced growth-related metrics. -
Feedback Sentiment Analysis - Individual Development Plan
Human Resources
Developed an NLP Ensemble Model based on VADER Sentiment and TextBlob Polarity Estimators to classify employee feedback into improvement themes that get assigned as learnings for the upcoming quarter. -
Inventory Classification and Analytics
Supply Chain
Classification model to segregate stock batches into slow-moving and expiring buckets to raise alerts on potential write-offs. -
Automation of Multiple Reporting Frameworks with End-to-End Smart Data Validations
Python empowered Excel tools to streamline data cleaning and processing with automated dashboards created using XLWings.
Data Science Intern
Piramal - Consumer Products Division
Jul 2021 - Dec 2021
(6-Month Internship)Mumbai, India
Data Science Intern in the Business Analytics Team that provides Analytics to the Business Functions of Sales, Finance, Supply Chain, HR, etc.
Worked on 2 main projects:
-
FP-Growth based Product Recommendation Engine
Sales Operations
Modeled a product recommendation engine on the FP-Growth Clustering Algorithm from scratch to recommend the next best product to be sold based on retailer's and hierarchical area's recent product sales. -
Salesmen Attrition Prediction using an Ensemble Model of XGBoost & Logistic Regression
Human Resources
Created an ensemble ML model to predict the probability of salesmen's attrition based on similar behavioral and performance metrics in previous attritions.
Education
Master of Science in Data Science
University of Virginia, School of Data Science
Jun 2024 - May 2025
Capstone Project:
- Implementing Multi-Modal RAG based LLM for Education
Sponsored by LMI
Research on methods to leverage Lecture PDFs, Slides & Videos in LLMs to develop an enhanced, context-rich learning experience
- Statistical Learning
- Bayesian Machine Learning
- Deep Learning
- Large Language Models
- Big Data Systems
- Ethics in Big Data
- Foundations of Computer Science
- Linear Models
- Practical Applications in Data Science
- Programming for Data Science
- Data Science Ambassador
- Resident of the Academic Village - The Range
- Monte Carlo Simulator
- Financial Independence Analysis
- Literature Review - Ethical Frameworks around Deepfake and GenAI
- Review - European Union AI Act
Bachelor of Engg. Mechanical Engineering
Minor in Data Science
Birla Institute of Technology & Sciences (BITS Pilani)
2018 - 2022
Relevant Coursework:
- Foundations of Data Science
- Applied Statistical Methods
- Engineering Optimization
- Non-Linear Optimization
- Control Systems
- Machine Learning
- Artificial Intelligence
- Swaranjali (Classical Music Club)
- Sanskrit and Foreign Languages Club (SaFL)
- Astronomy Club (AdAstra)
- Department of Sponsorship & Marketing (DoSM)
- Genetic Algo based Emotion Detection
- Computer Vision Based Real-Time Object Detection
- Swarm Robotics - Collaborative Object Collection
Personal Projects
This is a list of projects where I combine multiple interests and curiosities into learning pieces.
