Hey,I’m Shiva Sankari V A
I turn messy healthcare data into clear insights, interactive dashboards, and production-ready ML models. I’m building a portfolio that shows I can do the whole pipeline — from raw data → model → deployment — aiming for top-tier internships at companies like Jane Street, Meta, Google, and Stripe.
Quick Hits
- Current: 4th semester, Integrated M.Sc. Data Science
- Focus: Machine Learning · Healthcare Analytics · Predictive Modeling · ETL · Deployment
- Pro: clean code, reproducible notebooks, deployable demos (Streamlit / FastAPI)
- Goal: land top internships & build impactful healthcare ML products
Tech Stack
Languages:Python · SQL
Libraries / ML:NumPy · Pandas · Scikit-learn · Statsmodels
Viz / Dashboards: Matplotlib · Seaborn · Plotly · Streamlit
Deployment / Tools: FastAPI · Docker · Git · GitHub · Jupyter
Other basic PySpark / ETL concepts, time-series tools
Featured Projects
Disease Risk Predictor— full ML pipeline predicting disease probability from biomarker data (EDA → feature engineering → model → Streamlit demo).
Patient Readmission Classifier— reduce readmission risk using interpretable models + SHAP explanations.
Medical Cost Forecast- time-series forecasting of treatment costs (ARIMA + LSTM hybrid).
Health Analytics Dashboard — interactive Streamlit dashboard for hospital KPIs and alerts.
Clinical Data Toolkit — reusable cleaning & validation utilities for messy clinical datasets.
✅ What I Care About
- Reproducibility: seed values, env files, requirements
- Clarity: short notebooks + modular scripts
- Impact: metrics that matter (AUC, RMSE, precision/recall, cost savings)
- Explainability: model interpretation (SHAP / LIME)
- Deployability: one-click demos with Streamlit / FastAPI + Docker
Currently Learning & Building
- Advanced feature engineering for clinical time-series
- Model interpretability (SHAP, counterfactuals)
- MLOps basics: Dockerized deployments + CI for ML projects
- Probability & statistics for stronger quant intuition
Connect / Collaborate
- LinkedIn: www.linkedin.com/in/shiva-sankari-v-a-36b730315/
- GitHub: github.com/shivasankari27
Fun Fact I get excited by datasets that look impossible at first glance — the messier, the better. Also, coffee + late-night debugging is my cardio.