|
priyanshu = {
"role" : "Software Engineer & ML Researcher",
"based_in" : "Lucknow, Uttar Pradesh, India",
"education" : "B.Tech CSE @ DSMNRU (2023–2027)",
"focus" : [
"MLOps Pipelines",
"Predictive Modeling",
"Data Analytics",
"ML Engineering",
],
"currently" : "Shipping ML pipelines at 89%+ accuracy",
"research" : "Lead Researcher — Nifty 50 Volatility "
"Forecasting, presented at NCMPCS-2026",
"target_roles": [
"Machine Learning Engineer",
"Data Analyst",
"Data Scientist",
],
"fun_fact" : "Tea-powered coder ☕ — no deploy without a cup",
}I'm a performance-focused engineer who enjoys turning messy, real-world data into production-ready systems from statistical models to interactive dashboards that stakeholders actually use. Portfolio |
Data Science & ML Model Building Intern · BeeSkilled (Remote) · 06/2026
- Solved real-world dataset problems through end-to-end pipelines using a 6-stage data engineering process
- Built predictive regression models to forecast sales volumes and analyzed market segments
- Delivered an interactive Power BI dashboard with KPI blocks for stakeholders
Data Analysis Intern · Science Tech Institute (UP-Gov) · 07/2025
- Analyzed real-world government datasets using Python, Pandas, and R
- Built dynamic Power BI dashboards and a statistical processing system for predictive analysis
Predictive Modeling of Nifty 50 Volatility Using India VIX and ML Lead Researcher — Presented at NCMPCS-2026, DSMNRU, Lucknow · 03/2026
- Forecasted Indian market volatility using live NSE/BSE datasets (API + BeautifulSoup4)
- Applied Random Forest & Gradient Boosting; validated with RMSE, MAE, and R²
| Project | Stack | Highlights |
|---|---|---|
| Real Estate Valuation Analysis | Python, Scikit-learn, Streamlit, Plotly | 89.54% accurate ensemble AVM (Ridge, Lasso, Gradient Boosting) · MAE of $12,804 across 1,460 records, 79 features |
| Bibliophile Data Extractor | Python, Scikit-learn, BS4, Lxml | End-to-end scraping → cleaning → prediction pipeline · 75%+ accurate CLI ML system |
| Xela Arcade | Next.js, TypeScript, Chess.js | Retro gaming hub (Chess, Snake, Tic-Tac-Toe) with AI logic & real-time state management |
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