M.Sc. Physics + B.E. Computer Science · BITS Pilani, Goa · 3rd Year
I work across data analytics, applied machine learning, and computational physics — building systems that turn data into decisions.
Currently implementing DMRG for quantum many-body systems, focusing on CUDA-accelerated tensor contractions and MPS compression (under faculty supervision, code not yet public).
Previously built a production LLM system at CultureVo with Judge LLM evaluation and real-time feedback loops.
- Built an end-to-end restaurant analytics dashboard using Streamlit
- Performed cohort analysis to understand customer retention behavior
- Developed pricing intelligence to identify optimal pricing ranges
- Designed location opportunity scoring to identify high-potential markets
- Tools: Python, pandas, SQL, Streamlit
- Analyzed customer retention, churn, and purchasing behavior on e-commerce data
- Implemented cohort analysis, funnel analysis, and RFM segmentation
- Derived insights to identify high-value customers and improve retention
- Built an interactive dashboard for exploration and decision-making
- Tools: Python, SQL, pandas, Streamlit
- Building a system to match resumes with job descriptions and generate skill gap roadmaps
- Integrating LLM-based evaluation with structured scoring pipelines
- Tools: Gemini API, Python, Streamlit
Data Analytics: Python, pandas, SQL, Streamlit
Machine Learning: scikit-learn, NumPy, SciPy
Systems / Performance: CUDA, C/C++
Tools: Git, Linux
Email: nihalshriv694@gmail.com
LinkedIn: https://www.linkedin.com/in/nihalshriv/