Open to full-time roles from January 2027: Quant Research & Development · Capital Markets & Trading Analyst · Risk (Market, Credit, Counterparty, Liquidity) · Credit & Investment Analyst · Portfolio Analytics & Valuation
📧 aryansiwach1103@gmail.com · LinkedIn
Master of Quantitative Finance candidate at Rutgers Business School (Dec 2026) · B.S. Computer Science, Purdue University (2025). I build quant research pipelines on institutional data (WRDS: CRSP, Compustat, IBES, OptionMetrics, TAQ), covering derivatives pricing, volatility surfaces, factor investing, tail risk and execution.
Python · C++ · SQL · R · pandas · NumPy · SciPy · statsmodels · scikit-learn · FastAPI · Docker · AWS
I came to finance through computer science, so I build research the way an engineer would: point-in-time data, no look-ahead bias, every result reproducible from one script, and tests that check the numbers.
- 🎓 Now: Master of Quantitative Finance at Rutgers, focused on derivatives, fixed income, credit risk and Bayesian statistics
- 💼 Business Development Analyst (Data & Automation), Timestamp LLC: I automate lead generation with Python pipelines, cutting prospect research from 10 hours to 10 minutes
- 🤖 Software Development Intern, Engineta LLC: Improved NLP model accuracy by 15% and cut latency by 20%, then deployed the models on AWS EC2
- 👕 Co-founder, ACKTUS: I run the finances for a direct-to-consumer clothing brand with 1,000+ units sold
- 📈 CME Group University Trading Challenge: Returned 5% on a simulated $100K futures portfolio
- 🌱 Purdue Student Government: As Director of Sustainability, managed a $25K+ budget
6 Coursera specializations and 35 course certificates, all verifiable on Coursera.
| Certification | Issuer | Year |
|---|---|---|
| Financial Engineering and Risk Management Specialization (5 courses): Introduction to Financial Engineering and Risk Management · Term-Structure and Credit Derivatives · Optimization Methods in Asset Management · Advanced Topics in Derivative Pricing · Computational Methods in Pricing and Model Calibration | Columbia University | 2026 |
| Business and Financial Modeling Specialization (5 courses): Fundamentals of Quantitative Modeling · Introduction to Spreadsheets and Models · Modeling Risk and Realities · Decision-Making and Scenarios · Business and Financial Modeling Capstone | The Wharton School, University of Pennsylvania | 2024 |
| Financial Markets (Robert Shiller) | Yale University | 2023 |
| Certification | Issuer | Year |
|---|---|---|
| AI For Business Specialization (4 courses): AI Fundamentals for Non-Data Scientists · AI Applications in Marketing and Finance · AI Applications in People Management · AI Strategy and Governance | The Wharton School, University of Pennsylvania | 2024 |
| Coding for Everyone: C and C++ Specialization (4 courses): C for Everyone, Part 1: Programming Fundamentals · C for Everyone, Part 2: Structured Programming · C++ For C Programmers, Part A · C++ For C Programmers, Part B | University of California, Santa Cruz | 2022 |
| Python (4 courses): Programming for Everybody (Getting Started with Python) · Python Data Structures · Using Python to Access Web Data · Capstone: Retrieving, Processing, and Visualizing Data with Python | University of Michigan | 2021 |
| Web Design for Everybody: Basics of Web Development & Coding Specialization (5 courses): Introduction to HTML5 · Introduction to CSS3 · Interactivity with JavaScript · Advanced Styling with Responsive Design · Web Design for Everybody Capstone | University of Michigan | 2022 |
| Certification | Issuer | Year |
|---|---|---|
| Google Digital Marketing & E-commerce Professional Certificate (7 courses): Foundations of Digital Marketing and E-commerce · Attract and Engage Customers with Digital Marketing · From Likes to Leads: Interact with Customers Online · Assess for Success: Marketing Analytics and Measurement · Think Outside the Inbox: Email Marketing · Make the Sale: Build, Launch, and Manage E-commerce Stores · Satisfaction Guaranteed: Develop Customer Loyalty Online | 2023 |
Competitions: CME Group University Trading Challenge, Futures Trader (Nov 2025 – Jan 2026)
| Project | What it does |
|---|---|
| volatility-surface-pde-pricing | Arbitrage-free SSVI surfaces on 13 years of SPX options, Dupire local vol, and a from-scratch Crank-Nicolson PDE pricer for barriers, digitals and Americans |
| equity-factor-portfolio-construction | 8 point-in-time US equity factors (CRSP/Compustat/IBES) and a walk-forward, net-of-cost horse race of 9 allocation methods, 1981–2024 |
| execution-market-microstructure | NBBO reconstruction, spread decomposition, concave impact and a queue-aware execution backtest on millisecond TAQ |
| portfolio-var-engine | Five backtested VaR/CVaR models (parametric, historical, GARCH-FHS, EVT) on a multi-asset ETF portfolio |
| derivatives-pricing-toolkit | Black-Scholes, binomial, Monte Carlo, Merton jump-diffusion and Heston models calibrated to real options data |
| momentum-screener-backtester | Composite-momentum ranking and long/short backtesting with a pytest suite |