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Aryan Raj S Singh | Portfolio

Hi, I'm Aryan Raj S Singh

Founder at Altrelic and data/ML engineer-in-training specializing in algorithmic trading research, time-series modeling, and predictive systems.

About Me

Founder at Altrelic and data/ML engineer-in-training with hands-on work in algorithmic trading research, time-series modeling, and low-latency data pipelines. Built vectorized backtesting frameworks, factor libraries, and risk controls while shipping predictive systems with measurable accuracy. Winner of Pitcher Perfect (₹50,000), TGS Global Summit semifinalist, and RBIH fintech initiative selectee. Currently seeking fintech and quantitative software engineering internships where I can build research tooling, production backtests, and scalable data services.

Skills

Python Java SQL pandas NumPy SciPy scikit-learn statsmodels Time-Series (ARIMA/Prophet) Monte Carlo Simulation Factor Modeling Walk-Forward Validation VS Code matplotlib Data Ingestion Risk Overlays

Projects

Tennis Match Winner Predictor

Developed a machine learning prediction system using Python, pandas, and scikit-learn. Engineered advanced features including: • Elo-style player ratings • Surface win rates • Head-to-head statistics • Recent performance form Achieved approximately **85% offline accuracy** and demonstrated real-world reliability with a **10/10 correct live prediction streak**. Implemented probability calibration, basic monitoring, and documented model limitations to reduce overfitting risk.

Roulette Outcome Simulator (Research)

Built a statistical simulation system using Markov Chains, Random Forest models, and Monte Carlo simulation. Studied long-term probability dynamics of roulette outcomes and tested prediction patterns. Achieved approximately **52% long-run accuracy** on even-money outcomes, representing an improvement over the standard 50% baseline. This project focused on statistical research understanding rather than real-world gambling usage.

Experience

Founder — Altrelic (Fintech / Trading Research)

Built an algorithmic trading research stack using Python, pandas, NumPy, and scikit-learn for signal generation, risk controls, and predictive modeling. Designed latency-aware data ingestion pipelines and modular factor libraries for scalable strategy research. Implemented vectorized portfolio accounting and walk-forward validation methods to test trading strategies reliably. Won **Pitcher Perfect (₹50,000)** to develop MVP and refined investor narrative, TAM estimation, and go-to-market strategy. Selected by RBIH for early-stage fintech innovation support.

Propulsion Engineer — Rocketry BMSCE

Led static-fire data capture and engineering analysis processes. Developed Python tooling to compute burn rate, thrust curves, and uncertainty measurements. Standardized technical checklists and safety workflows, improving reliability and operational safety practices.

Green Room & Guest Ops — Under 25 Summit

Managed backstage operations for artists, entrepreneurs, and guest speakers. Handled entry-pass validation, movement coordination, and access control operations. Ensured professional guest experience and supported event workflow efficiency.

Education

B.M.S. College of Engineering

Bachelor of Engineering — Computer Science & Data Science 2023 – 2027 Relevant Coursework: • Data Structures & Algorithms • Probability & Statistics • Machine Learning • Databases • Operating Systems

Awards & Activities

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