Presentation @ QF & Statistics PhD Webinar
I presented work from TIPS ETF whitepaper at SBU QF & Statistics PhD Webinar, featuring guests from Goldman Sachs and Renaissance Technologies
About Me
Data Scientist with 5 years of experience leveraging machine learning, analytics, and engineering to provide intelligent insight. Interested in the fields of causal inference, Monte Carlo, optimization, statistics, time-series analysis, computational mathematics, and simulation.
Featured Projects
Momentum Families Through Sequential Return Clustering
My paper explores new way to classify momentum and micro-regimes in time-series, using clustering as an alternative to autoregressive methods. (IN PROGRESS)
A Cost-Sensitive Optimization Framework for Alleviating Childcare Deserts
I co-authored a paper that optimally assigns childcare facilities to maximize facility access in NY counties with minimal cost (IEOR 4004)
TIPS ETF Whitepaper @ GlimmAnalytics
I co-authored a whitepaper with Dr. James Glimm that conducts extreme value analysis of iShares TIPS ETF & CPI to find signals for ETF share price and improve autoregressive models
Drawdown Beta Site
I co-developed website that features Conditional Drawdown At-Risk Beta, Expected Regret Drawdown Beta & more for all S&P 500 tickers
Education
- Columbia University - Fu Foundation School of Engineering and Applied Science
- M.S. Operations Research
- Stony Brook University - College of Engineering and Applied Sciences
- B.S. Applied Mathematics & Statistics
- B.S. Financial Information Systems
- Awards: Magna Cum Laude, Dean's List, Presidential Scholarship
Skills
Software
- Python
- R
- SQL (Snowflake, Server, SQLite, MySQL)
- Pytorch
- AWS
- HTML
- CSS
- JavaScript
- React
Math & Models
- LightGBM/XGBoost
- Gaussian Mixtures
- Granger Causality
- Non-linear Regression
- Imbalanced Learning
- Clustering
- Linear Programming & Optimization
- Stochastic Processes
Other
- Excel
- CI/CD (GitHub, GitLab, Jenkins)
- Financial Statements
- M&A Fundamentals
Courses
Mathematics
- AMS 320 - Quantitative Finance
- IEOR 4004 - Optimization Models & Methods
- AMS 301 - Finite Mathematical Structures
- IEOR 4106 - Stochastic Models
- AMS 341 - Operations Research: Deterministic Models
- MATH 004B - Differential Equations
- MATH 004A - Multivariable Calculus
- AMS 210 - Applied Linear Algebra
- IEOR 4150 - Probability & Statistics
- AMS 315 - Data Analytics
Engineering
- IEOR 4574 - AI & Digital Transformation
- ISE 305 - Database Design & Practice
- CSE 215 - Foundations of Computer Science
- ISE 339 - Benevolent Computing
- ESE 346 - Computer Communications
- IECE 213 - Data Structures & Algorithms
- CIS 043 - Software Development With Java
Other
- IEOR 4578 - Startup Fundamentals
- IEOR 4207 - Human Factors: Performance
- ISE 333 - User Interface Development
Specializations
- Prompting Essentials - Google
- Deep Learning with PyTorch - IBM
- Machine Learning Specialization - Stanford Online
- Bloomberg Market Concepts - Bloomberg