Result-Driven Data Scientist with 2 years’ experience designing & deploying AI/ML apps, vector-search recommendation systems, and AI/ML solutions that have:
- Boosted user retention 📈
- Reduced churn 💡
- Delivered actionable, data-driven impact for startups and research labs
I love making AI real for business & research—through GenAI, analytics, cloud pipelines, and rapid prototyping.
- 🧭 Vector Search Recommender (GradMeet): --> Deployed on AWS EC2, bringing in 500+ users and powering a 20% engagement increase
- 🧬 Genomics Analytics: --> Improved cluster quality by 18% (Silhouette), 68% (Davies-Bouldin)
- 🦾 Drug Synergy GNN: --> Integrated 23K drug–cell line pairs, reducing RMSE by 7%, boosting explainability by 2%
- 🤝 Churn Reduction: --> Cut churn by 15% via Power BI dashboards and A/B tests
- 🦠 COVID Lab Analytics: --> Analyzed 35K+ PCR records; led to 30% faster turnaround and 40% less backlog
EcoAction AI [Climate Sustainability Platform]
- 🌱 AI-powered platform for personal sustainability plans (LLMs + vector search)
- 🌐 Try the Web App | Source Code
Multi-Agent ArXiv Paper Discovery
- 🤖 Multi-agent LLM & CrewAI pipeline for automating discovery and analysis of thousands of ArXiv AI papers
- Source Code | Medium Article
Reddit Sentiment Analysis Pipeline
- 💬 Kafka/Spark pipeline, 70% faster analytics over 10+ subreddits, real-time dashboards
- Source Code
| Categories | ** Skills ** |
|---|---|
| 🗣️ Languages | Python (PySpark, Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch), SQL |
| 🤖 Gen AI | Hugging Face, Langchain, LLM (LORA/QLORA/PEFT), Crew AI, Quantization, LangGraph |
| ☁️ Cloud/Ops | AWS (EC2, ECS, Lambda, SageMaker, Bedrock), Azure, Streamlit, Docker, CI/CD, MLOps |
| 🏗 Data Eng/Ops | Spark, Airflow, Kafka, MySQL, PostgreSQL, MongoDB, ETL, Vector DB (FAISS/TypeSense) |
| 📊 Analytics | Power BI, Tableau, Excel, A/B Testing, Statistical Modeling, Time Series |
| 💼 Other Skills | Business Analysis, Root Cause, Issue Trees, Git, Tableau |
Data Scientist – GradMeet, LLC (Oct 2024 – May 2025)
- Launched AWS EC2-based vector search recommender (500+ new users, +20% engagement)
- Integrated NLP sentiment & regex-based feedback for personalizing user experience
- Built internal RAG for document retrieval; supported A/B testing and growth strategies
- Productionized analytics (AWS/Docker/CI/CD) for fast experiment iteration
Data Scientist – Indiana University Bloomington (Sep 2023 – Aug 2024)
- Enhanced spatial genomics, boosting cluster metrics (18%/68%) with advanced stats
- Developed GNN on 23K drug–cell line pairs (–7% RMSE, +2% R²)
- Streamlined 15,000+ RNA-seq sample validation, saving lab time (–15%)
- Presented complex data insights to stakeholders for biomedical research impact
Associate Instructor – Indiana University Bloomington (Jan 2023 – May 2023)
- Mentored 30+ students in ML project workshops; improved student performance by 2%
Research Data Analyst – Biostatistics Consulting Center (Aug 2022 – Dec 2022)
- Analyzed 35,000+ COVID PCR tests; reduced lab time by 30%, backlogs by 40%
- Built Power BI dashboards, automated reporting (10+ staff hours saved/week)
- Validated diagnostics with ANOVA/t-test for 99% accuracy
- M.S. – Data Science (2023), Indiana University, Bloomington, IN, USA
- P.G. Diploma – Data Science (2021), IIIT Bangalore, India
- B.S. – Computer Science (2019), Symbiosis International University, Pune, India
“Expand any section above for project demos and deeper detail. I’m passionate about scalable, real-world AI.”