Production‑ready engineer · Research‑level mathematics · Quant & ML builder
Actively exploring Quant Dev / ML Engineer / SWE roles
Message me on LinkedIn to chat.
- M.S. Mathematics - Stony Brook University (3 years PhD research)
- B.A./M.A. (Joint) Mathematics - Macaulay Honors College (full merit scholarship)
- The CUNY Graduate Center (17 PhD level math classes as undergrad)
- Research internships @ Cornell University and UC Santa Barbara
- Google FooBar - completed all 5 rounds (invitation only)
- Project Euler - top 1 % worldwide (username DilSingh)
- Presentations - 5 research talks & 18 graduate seminars (full list)
- Gillet Memorial Fund Award - top graduating math major, 2018
Quantitative finance projects
- OptPricing – Python library pricing option contracts, valuing rates, investigating implied volatility; features 15+ derivative models and advanced numerical algorithms
- forecast_vol - Attention‑based pipeline forecasting minute‑level volatility
- stochCalc - Symbolic & numeric calculus for Stochastic Differential Equation systems
- RMBS - Waterfall analytics for residential MBS structures
Some number theory projects
- primes – advanced primality testing and factorization methods
- ellipticCurve – computations over ℚ & finite fields
- ECM – elliptic‑curve factorization
Languages: Python | C++ | MySQL | MATLAB | Bash
Frameworks: NumPy | Pandas | SciPy | Numba/Cython | TensorFlow | PyTorch | scikit‑Learn | Optuna | Polars
DevOps: Git | CI/CD | Docker | REST APIs | Streamlit | Linux
Quant: Stochastic Calculus | PDE Approximations | Variance Reduction Methods | Monte Carlo Simulation | Lattice Methods
Certifications in Machine Learning (Stanford) and SQL for Data Science (UC Davis)