• Led the project from concept to production with warehouse operations and IT, delivering data driven automation and slotting optimization while enforcing role based access, environment separation, and secure data handling
• Designed and operated analytics workflows in dev and prod with secure CI/CD, basic vulnerability checks for containerized components, coordinated patching with platform teams, and ensured stable handover to operations.

• Coordinated a team of four engineers reviewing and improving production ready Python code for data processing, data visualization and API based services.
• Managed task allocation and delivery across parallel workstreams, ensuring consistent quality, clear documentation and on time completion.

System for digitalizing daily warehouse workforce planning using workload based allocation, structured data processing, and repeatable operational execution.

• Contributed to development and operationalization of machine learning based predictive model for budget planning, achieving 94% accuracy for 12 month forecasts and reducing manual planning effort.
• Automated analytics pipelines across multiple internal data sources with dev and prod separation, coordination with enterprise IAM and Active Directory based access controls and documented runbooks to support secure operations and audits.
• Configured and utilized APIs for data integration from TM1 and SAP systems, supported vulnerability and patch compliance and ensured reporting access followed Active Directory role assignments and least privilege principles.

• Built an internal Q&A solution to support BI operations and HR workflows, integrating a controlled knowledge base with role based access and basic data protection checks for sensitive content.
• Developed and maintained API integrations for a web app deployment across 15+ cloud environments, with standard logging, monitoring and secure configuration practices to support stable operations.

• Improved operational KPIs by automating data flow and analytics across 18 warehouses and six sales channels, reducing manual effort by around 4 hours per day for two analysts and improving reporting consistency.
• Implemented reliable API based data integrations with structured logging, controlled access to datasets and documented runbooks to support stable operations across environments.

• Developed Random Forest classifier with 88% accuracy, trained & evaluated on a large dataset of tweets to detect hate/offensive tweets by leveraging different NLP techniques, built web app to facilitate reporting of flagged tweets.
• Developed a conversational Q&A chatbot using LangChain and OpenAI, leveraging chromaDB as vector store and streamlit to develop an interface that required PDFs as inputs and the chatbot answered questions related to the PDF