Kunal K.Private profile: Upwork shows its earnings only to signed-in members, so we check it every few weeks, not daily. MRR here is a rough estimate (Upwork's six-month earnings ÷ months active). Last read Nov 5, 2026.

I’m a Mathematics & Computing (Integrated M.Sc.) graduate(CGPA- 9.67) from IIT with professional experience in machine learning, quantitative research, data science, and software engineering. I specialize in building mathematically rigorous, data-driven systems that move cleanly from research to production. My work sits at the intersection of advanced mathematics, ML/AI, and real-world engineering—allowing me to not only design sophisticated models, but also validate, optimize, and deploy them reliably in production environments. 🔹 What I Do Machine Learning & Data Science Predictive modeling, feature engineering, and statistical learning Time-series analysis, forecasting, and model validation ML pipelines in Python (NumPy, Pandas, Scikit-Learn, PyTorch) Quantitative Research & Finance Systematic trading strategy design and backtesting Alpha research: mean reversion, momentum, statistical arbitrage Portfolio optimization using Black-Litterman, Glasso, meta-heuristics Risk modeling, Sharpe optimization, drawdown control Reinforcement Learning & Optimization RL-based decision systems (DQN + LSTM) Meta-heuristic optimization (PSO, Simulated Annealing) ML-driven asset allocation and strategy optimization Software & Backend Engineering Production-grade Python and Java development Backend services with strong testing, CI/CD, and reliability guarantees Clean, modular, well-documented, performance-optimized code 🔹 Professional Experience Development Engineer — Standard Chartered GBS (Full-Time) Built secure, high-quality backend services for financial platforms Migrated large codebases from Java 8 → Java 17, improving performance and maintainability Increased automated test coverage to ~60% across multiple repositories through robust unit and integration testing Brain Research Consultant — WorldQuant Designed and optimized 30+ alpha strategies, achieving Sharpe ratios up to 3.0 Controlled pairwise correlation and improved robustness of signals Focused on Sharpe ratio, ROE, and risk-adjusted performance Quantitative Researcher — Indxx Private Limited Built ML-driven portfolio optimization frameworks Combined Particle Swarm Optimization and Simulated Annealing Improved portfolio Sharpe by 10% and reduced risk metrics by 12% Mathematics Expert — Micro1 (Freelance) Designed high-difficulty, original mathematical problems Created Project Euler–style challenges with competition-grade rigor 🔹 Selected Client Engagements (Upwork & Contract Work) Quantitative Validation & Automation Architect — Æthux (Atlas Project) Architected a production-grade validation, explainability, and CI/CD framework for quantitative investment models Built deterministic test harnesses for Black-Litterman and Monte Carlo engines Implemented model explainability (SHAP/LIME), drift detection, and automated evidence pipelines Delivered an auditable, compliance-ready analytics stack used for production decision-making Macro Economist — Inverse Financial Model & TAM Study Developed an inverse financial model for a novel digital marketplace Conducted a comprehensive Total Addressable Market (TAM) analysis Co-authored a white paper detailing economic incentives and market dynamics (Details shared within NDA constraints.) 🔹 Research & Technical Projects Neural Black-Litterman Model (Master’s Thesis) Integrated LSTM-based return forecasting with Black-Litterman allocation, achieving 25.3% annualized returns and strong risk-adjusted performance on NIFTY & S&P 500. Advanced Statistical Arbitrage with Reinforcement Learning Implemented OU, distance-based, and RL-driven mean-reverting strategies using DQN + LSTM. Cryptocurrency Momentum & Reversal Strategies Identified short-term reversals and long-term momentum with Sharpe ratios up to 3.0. Robust Glasso Portfolio Optimization Improved Sharpe by 13.7% and reduced turnover using robust precision matrix estimation; research paper under review. 🔹 Tools & Skills Languages: Python, Java, C, C++, SQL ML / Data: NumPy, Pandas, Scikit-Learn, PyTorch, Backtrader Backend & Dev: Spring Boot, GitHub, CI/CD, JUnit, Mockito Math & Stats: Probability, Stochastic Processes, Optimization, Time Series, Financial Mathematics