Data engineer and ML practitioner, currently doing my Master's in Data Science at Arizona State University (GPA 3.89). Before grad school, I spent 2 years at Shell building data pipelines and migrating enterprise dashboards β now I'm deep into AI/LLM engineering.
Shell (2023β2025, Associate Data Engineer) β Worked on SAP HANA views for trading and supply projects, cutting data processing time by 15%. Built a Python automation to catch data discrepancies during a large S/4 HANA migration.
Bosch (2023, Data Science Intern) β Built a logistics heuristic model in Python + Streamlit that reduced delivery times by 12%. Also did HR sentiment analysis using VADER on Great Place to Work data.
Deloitte (2022, Tax Technology Intern) β Built an ASP.NET web app that sped up tax data uploads by 30%, and Power BI dashboards used by 10+ stakeholders.
π€ Compliance Intelligence Platform β A RAG-based AI system that lets you query legacy financial policy documents and get citation-backed answers. Built with LangChain, OpenAI embeddings, and Qdrant. Uses hybrid search (vector similarity + BM25) with cross-encoder reranking to stay precise and avoid hallucinations.
π AI Trading Strategy Generator β Built for the AI Society at ASU. Describe a trading idea in plain English β Gemini API converts it to executable Python β backtests it against historical stock data β shows Sharpe ratio, max drawdown, and cumulative returns.
| Languages | Python, SQL, C/C++, Julia |
| AI / LLM | RAG, LangChain, OpenAI, Gemini, HuggingFace, Qdrant, ElasticSearch |
| Data Engineering | Databricks, PySpark, Delta Lake, SAP HANA, Azure |
| Visualization | Power BI, Streamlit, Tableau, SAP Analytics Cloud |
| Backend / DevOps | FastAPI, Docker, MLflow, Flask |
π§ kmanav262@gmail.com Β Β·Β LinkedIn