📍 Raipur, Chhattisgarh, India · B.Tech CSE (Data Science) · Amity University · CGPA 7.45 · 2026 Graduate
| Domain | Maturity | Focus |
|---|---|---|
| Retail Analytics | ██████████ | RFM · CLV · Cohort · Basket |
| Financial & Risk | ██████████ | VaR · Monte Carlo · Sharpe |
| Healthcare Analytics | ████████░░ | Readmission · Utilization |
| Supply Chain | ████████░░ | Demand · Route Optimization |
| Cloud Analytics | ███████░░░ | AWS S3 · Athena · QuickSight |
| Big Data Engineering | ███████░░░ | PySpark · Distributed Processing |
| Problem | Fragmented transactions → untargeted marketing |
| Analytics | RFM Segmentation · Cohort · Market Basket · CLV |
| Stack | Python · SQL · Power BI |
| Status | Completed |
| Repo | Consumer-360 |
| Problem | Missing institutional-grade risk visibility |
| Analytics | 10k+ Monte Carlo · VaR · Expected Shortfall |
| Stack | Python · MongoDB · Streamlit · Plotly |
| Status | Completed |
| Repo | AlphaPulse |
| Problem | Manual, error-prone attendance processes |
| Analytics | Face Recognition + RFID · Anomaly Detection |
| Stack | Python · Luxand API · RFID · IoT |
| Status | Completed · Live |
| Repo | EduVista |
| Problem | Fragmented restaurant trend data across India |
| Analytics | NLP Sentiment · Geospatial Intelligence |
| Stack | Python · Streamlit · Plotly · NLP |
| Status | Completed |
| Repo | ZomatoLens |
| Problem | Manual risk-return allocation inefficiency |
| Analytics | Efficient Frontier · Monte Carlo · Sharpe |
| Stack | Python · SQLite · Power BI |
| Status | Completed |
| Repo | Portfolio Optimization |
| Problem | Unclear drivers of vehicle fuel efficiency |
| Analytics | EDA · Clustering · Classification · Regression |
| Stack | Python · Scikit-Learn |
| Status | Completed |
| Repo | Fuel Economy |
| Problem | High latency & limited visibility into readmission risk and bed utilization |
| Architecture | AWS S3 Data Lake → Athena → QuickSight / Power BI |
| Stack | AWS S3 · Athena · PySpark · SQL · Power BI · QuickSight |
| Status | In Progress |
| Value | Query latency 45 min → <90 sec on ~2 TB simulated data |
| Problem | Need for scalable demand forecasting and route intelligence |
| Architecture | PySpark → Spark SQL / Parquet → Streamlit + Plotly |
| Stack | PySpark · Spark SQL · Parquet · Streamlit · Gemini API |
| Status | In Progress |
| Value | First-run load ~38 s → ~3.6 s |
flowchart LR
A[Raw Sources] --> B[Ingestion]
B --> C[Processing]
C --> D[Modeling]
D --> E[BI Layer]
E --> F[Decisions]
style A fill:#0F2027,color:#fff,stroke:#2C5364
style B fill:#203A43,color:#fff,stroke:#2C5364
style C fill:#2C5364,color:#fff,stroke:#2C5364
style D fill:#34718A,color:#fff,stroke:#2C5364
style E fill:#3E8FA9,color:#fff,stroke:#2C5364
style F fill:#4BA3C3,color:#fff,stroke:#2C5364
timeline
title Riddhima Singh | Academic & Professional Journey
2019-20 : Class 10 – Carmel Public School (ICSE)
2021-22 : Class 12 PCM – Aditya Birla Public School (CBSE)
2022-26 : B.Tech CSE (Data Science) – Amity University Chhattisgarh
2024 : Summer IT Intern – UltraTech Cement (Baikunth)
2025 : Data Analysis Intern – Cognifyz Technologies
2025 : Summer Trainee – BSNL Western Telecom Region
2026 : Data Analytics Associate (L1) – Infotact Solutions
2026 : Graduation – CGPA 7.45 / First Division
| Category | Technologies |
|---|---|
| Programming | Python · SQL · JavaScript |
| Analytics | Pandas · NumPy · SciPy · Scikit-Learn |
| Visualization | Power BI · Tableau · Plotly · Streamlit |
| Databases | MySQL · SQLite · MongoDB |
| Cloud | AWS S3 · AWS Athena · QuickSight |
| Big Data | PySpark · Spark SQL · Parquet |
| AI & Automation | OpenAI · Gemini · Claude · Hugging Face · n8n · Zapier |






