DEVIPRASAD NIRJOGI
Hyderabad
Summary
Dynamic research consultant with a proven track record at World Quant, specializing in machine learning and statistical modeling. Developed high-Sharpe ratio models and innovative alpha strategies. Adept at leveraging Python and SQL to drive impactful insights, while demonstrating strong analytical skills and a commitment to excellence in quantitative finance.
Overview
1
1
year of professional experience
Work History
Roopastra
Founding Member
Hyderabad
12.2024 - Current
- AI-powered virtual try-on prototype, architecting the core solution with Python and Computer Vision to successfully demonstrate real-time garment overlay capabilities.
- Engineered the initial machine learning models for body detection and created a proof-of-concept for an AI-driven, occasion-based style recommendation engine tailored for the Indian retail market.
- Established the company's competitive advantage by leading in-depth market analysis and defining a unique selling proposition based on real-time processing, cultural relevance, and a hardware-light model
Research Consultant - Remote Internship
World Quant
01.2025 - Current
- Created novel alpha strategies across multiple asset classes and timeframes
- Developed and backtested quantitative models for global equities markets
- Implemented machine learning techniques to enhance alpha signal generation
- Conducted research on market anomalies and factor-based investment strategies
- Contributed to the firm's alpha library with several high-Sharpe ratio models
- Worked with 200+ financial vector datasets
Education
Bachelor of Science -
Indian Institute of Technology
Madras05-2026
Skills
- Python
- SQL
- Statistical modeling
- PineScript
- Interactive Brokers
- Machine learning
- Time Series Forecasting
- Deep Learning
Projects
Option Pricing Toolbox | Python, NumPy, Matplotlib, Jupyter
- Implemented Black-Scholes-Merton model with comprehensive Greeks computation for accurate derivative pricing.
- Built implied volatility surface estimator utilizing real market data for enhanced pricing accuracy. Simulated path-dependent options using Monte Carlo methods for complex derivative valuation.
Portfolio Optimization | Python, CVXPY, Pandas
- Developed mean-variance portfolio optimizer with advanced risk constraints and comprehensive backtesting for Stocks and Cryptocurrency
- Integrated Sharpe ratio and Sortino ratio maximization with robust backtesting module for performance analysis. Added EigenVector optimization model extension for maximum returns of the portfolios.
Accomplishments
- Quantageddon 2025 - First place
- WorldQuant PowerPool Alphas 2025- Winner
- 50kafunda - Winner
Timeline
Research Consultant - Remote Internship
World Quant
01.2025 - Current
Roopastra
Founding Member
12.2024 - Current
Bachelor of Science -
Indian Institute of Technology
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