Welcome to my GitHub profile!
I am a Data Scientist and Data Engineering professional with hands-on experience building end-to-end machine learning systems, demand forecasting models, and scalable analytics platforms.

My work focuses on real-world business problems, especially in retail, supply chain, and operations, where data quality, interpretability, and production reliability matter as much as model accuracy.

• 🔹 Specialization: Forecasting, ML systems, analytics platforms
• 🔹 Domains: Supply Chain, Retail, Promotions, Inventory
• 🔹 Mindset: Business-first, production-aware
• ⚡ Fun fact: Most forecasting failures are data problems, not model problems 😉

Python	PySpark	TensorFlow	Snowflake	SQL	FastAPI
Docker	Azure	CI/CD	ML	Databases

Technology Overview
I work across data science, data engineering, and MLOps, building systems that move from raw data → validated datasets → ML models → production deployment.
Strong emphasis on data quality, scalability, and monitoring.

• Demand forecasting (seasonality, promotions, sparse data)
• Promotion impact & causal inference
• Feature engineering for time-series & ML
• Data quality frameworks & anomaly detection
• Scalable ETL pipelines (Spark, SQL)
• ML deployment & monitoring

Certifications:
Here are some of my most reputed certifications that reflect my expertise in data science, machine learning, and AI technologies:

• Gen AI workshop – Indian Institute of Technology, Hyderabad (Issued April 2025)
• Machine Learning – Cornell University (Issued April 2023)

For more certifications, feel free to check my LinkedIn Profile.

• Forecasting limited-history and event-based products
• Hierarchical & global ML models
• Promotion uplift and scenario forecasting
• Business KPIs: service level, stockouts, excess inventory

• Multi-tenant, configurable validation engine
• 20+ data quality checks
• Built using Python & PySpark
• Supports Snowflake and SQL Server
• Cloud-deployable

• ML-based supplier evaluation
• Reliability, quality, lead time, and risk signals
• Decision-support dashboards

• Automated detection of unusual patterns
• Sales, inventory, and supply chain KPIs
• Reduces blind spots in operational reporting

💡 Explore my repositories for clean code, architecture diagrams, and production-oriented ML designs.

I enjoy working at the intersection of data, business, and engineering.
If you’re interested in collaboration, architecture discussions, or real-world ML systems — feel free to connect.