📧 [email protected] | 📱 +91-9952188901 | 💼 LinkedIn | 🐙 GitHub

I'm a Senior Data Scientist at Target who loves turning messy data into clean insights (and occasionally turning coffee into code ☕). I specialize in Retail Analytics, Time Series Forecasting, and building ML solutions that actually work in production.

When I'm not optimizing planograms or training models, you can find me analyzing stock charts, building my dream PC rig, or re-watching Silicon Valley

Languages: Python, SQL

Forecasting: Prophet, SARIMAX, Exponential Smoothing, NHITS, LSTM, GAMs.

Modeling & AI: xgboost, svm, hdbscan, k_means, ViT, BERT, SAM, transformers.

ML Engineering: Docker, Git, MLflow, PySpark, Software Design

GEN AI: langchain, langgraph, adk, langfuse, LORA.

Cloud & CI/CD: AWS, GCP, Jenkins, Github Actions

Statistics: Elasticity Modeling, Simulations, Hypothesis Testing, Montecarlo, Casual Analysis

Senior Data Scientist (Mar 2025 - Present)

• Integrated POE (planogram operational efficiency) datasets into planogram optimization
• Building elasticity models and simulations framework for estimating backstock labor and lost sales with respect to pog capacity.
• Developed Agentic AI for end-to-end POG build with successful trial on one category

Data Scientist (June 2022 - Mar 2025)

• Forecasted store labor requirements 4 weeks in advance with 85% accuracy, saving $10M/year
• Developed demand-driven backfill strategy yielding $5M total benefit
• Conducted market basket analysis for data-driven store layout changes
• Utilized Generative AI for customer review summaries and product quality insights
• Predicted stock zero adjustments with 80% precision using tree-based models, expected to increase sales by $3M

Data Scientist (May 2021 - June 2022)

• Designed and integrated forecasting models (Prophet, Exponential Smoothing, ARIMA) achieving <20% MAPE
• Developed Monte Carlo simulations for clinical trial planning, used by 300+ users.

Product Engineer (Data Science) (October 2019 - May 2021)

• Created "what-if" regression analysis features for analytics products
• Identified actionable insights through deep event cause analysis
• Implemented anomaly detection in sales data using PySpark

Data Analyst Intern (April 2019 - September 2019)

• Built scalable KPI calculation system for large customer databases using Spark
• Managed ETL operations and developed APIs for KPI calculation and forecasting

⭐ $10M Annual Savings - Labor forecasting with 85% accuracy

⭐ $5M Benefit - Demand-driven backfill optimization

⭐ $3M Expected Sales Increase - Stock adjustment prediction with 80% precision

⭐ 300+ Users - Monte Carlo simulation tool for clinical trials

⭐ <20% MAPE - Integrated forecasting engine

⭐ GenAI Solutions - Customer insights and product quality automation

📜 Master of Technology (MTech) in Data Science and Engineering Birla Institute of Technology and Science, Pilani (2022 - 2024)

🎓 Bachelor's Degree in Computer Science Mepco Schlenk Engineering College (2015 - 2019)

🔹 4+ years in Retail Domain expertise across store operations, supply chain, and merchandising

🔹 6+ years combined professional experience from intern to Senior Data Scientist

🔹 Multiple domains: Retail, Clinical Trials, Analytics Products

Feel free to reach out to discuss Data Science, Stock Markets, or why Jinx deserves better. Let's build something cool together! 🚀