Open to Opportunities

Prabuddha Tamhane.

Data Scientist | Financial Analytics

Building data-driven solutions at the intersection of finance and machine learning. Master's candidate at UBC with a unique dual MBA-Tech background.

+18.65% 4-Month Return (Live)
4.3M+ Data Points Processed
3 Models Competing Live
View Projects Get in Touch
Momentum Strategy S&P 500
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About Me

I'm a data scientist with a deep-seated passion for finance and technology, currently pursuing a Master of Data Science at the University of British Columbia.

My background is uniquely positioned at the intersection of quantitative analysis and software engineering. I hold a dual degree from NMIMS: an MBA in Finance and B.Tech in Computer Engineering, giving me both the financial intuition and technical depth to build sophisticated data-driven solutions.

I build production-grade systems: automated trading algorithms, predictive models for healthcare, and high-volume data pipelines. Focused on data science and financial analytics roles.

Master of Data Science, UBC (2025-2026)
MBA Finance + B.Tech Computer Engineering
Published Research in Predictive Modeling
Prabuddha Tamhane
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Featured Projects

Featured Project

Paper Trader AI

I built a trading system that runs itself. Three strategies compete head-to-head on the S&P 500: momentum, XGBoost, and LSTM. Backtested on 9 years of data, now running live with automated daily trades.

Live results (Oct 2025 – Jan 2026): Momentum leads at +18.65% return (vs SPY +3.94%), 2.04 Sharpe. Paper trading only.

+18.65% Best Return
2.04 Sharpe Ratio
3 Models Live
4.3M+ Data Points
  • Python
  • XGBoost
  • TensorFlow
  • Pandas
  • GitHub Actions
  • Streamlit
Live Dashboard GitHub
Technical Details & Risk Metrics
Risk Management
  • Max Drawdown: -9.1% (vs SPY -5.1%)
  • Stop-Loss: 15% per position
  • Position Limits: 15% per stock, 30% per sector
  • Transaction Costs: 5 bps slippage modeled
Strategy Breakdown
  • Momentum: 12-1 month price factor (Fama-French)
  • ML: XGBoost + 15 features (RSI, MACD, etc.)
  • DL: LSTM with 60-day sequences
  • Universe: S&P 500 (503 stocks)
Engineering
  • Tests: 75 unit tests with CI/CD
  • Automation: 6 GitHub Actions workflows
  • Infrastructure: Docker-ready, SQLite cache
  • Data Quality: Point-in-time universe (no look-ahead bias)
paper-trader 
# Paper Trader AI - Live Performance
$ python main.py --status

System:  LIVE since Oct 2025
Leader:  Momentum +18.65% (SPY: +3.94%)
Sharpe:  2.04 | Excess: +14.71%

All 3 models running autonomously.
View live dashboard for real-time updates →

Brain Tumor MRI Classification

Deep learning classification model using KNN, SVM, CNN, and VGG16 on 3,200+ brain MRI scans. Achieved 98% accuracy in tumor detection.

  • TensorFlow
  • Scikit-learn
  • OpenCV

Mumbai Transit Forecasting

Real-time passenger traffic prediction system using ARIMA and YOLOv5 object detection, forecasting up to 30 minutes ahead with 95% detection accuracy.

  • Python
  • ARIMA
  • YOLOv5

Employee Attrition Prediction

Published research comparing Logistic Regression, Decision Tree, and Random Forest for HR analytics, achieving 91% prediction accuracy.

  • Python
  • SPSS
  • Scikit-learn
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Experience

Business Analyst Intern

Prudent Corporate Advisory Services
May 2024 - Sep 2024
  • Analyzed 5+ years of historical performance data for 50+ mutual funds to develop a data-driven model, improving product basket construction by 15%
  • Built a business expansion model using Python and SQL for geospatial and revenue forecast analysis across 10 markets
  • Conducted deep-dive revenue analysis across 15 branches and 4 sectors, identifying key performance drivers
Python SQL Financial Analysis

Software Development Intern

Datamatics Global Services
May 2023 - Jun 2023
  • Authored and optimized complex SQL stored procedures handling 10,000+ daily transactions, reducing query latency by 25%
  • Implemented dynamic data filtering and visualization using JavaScript and ASP.NET MVC, reducing report generation time by 40%
SQL JavaScript ASP.NET
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Technical Skills

Languages

Python SQL R C++ C Bash

Machine Learning

TensorFlow XGBoost Scikit-learn Time-Series Forecasting Computer Vision (YOLOv5)

Cloud, MLOps & Tools

AWS (Lambda, S3, ECR, EventBridge) Docker GitHub Actions (CI/CD) Streamlit Git PostgreSQL Excel (VBA) PowerBI Tableau

Financial Engineering

Algorithmic Trading Backtesting Factor Investing Risk Management (VaR, Drawdown Control)
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Get In Touch

I'm actively seeking opportunities in data science, quantitative analysis, and financial analytics. Whether you have a role in mind, a project to discuss, or just want to connect, I'd love to hear from you.

prabuddha.tamhane@gmail.com