• Founded a quantitative research and asset management company
• Leads a team of interns working on quantitative programming and research projects
• Creates, tests, and deploys statistical, ML-based, and AI-based models to describe and predict stock prices using Python and R
• Creates algorithmic trading strategies in Python
• Performs portfolio management techniques to enhance returns or reduce risks uses constrained optimization techniques in Python, R, and Matlab
• Creates trading software applications to automate trade operations using Django

• Mentors six to seven teams of six senior undergraduate students as they work with industry partners to design, create, test, and deploy a software project over the course of their senior year.

• Led a team of eight FP&A analysts and managers
• Used accounting, finance, and data engineering experience to create monthly internal financial reporting for Verizon's executive team
• Led the creation and deployment of automated reporting processes
• Created reporting visualizations and dashboards for executives
• Designed, deployed, and delivered FP&A insights regarding Verizon's capital expenditures to Verizon's executive team

• Tutors students in "Research Methods in Finance", an graduate-level introductory financial statistics class, on statistical concepts, financial research principles, and the use of the R language

• Designed and deployed explanatory and predictive models to optimize the captial expenditure policy for Verizon's network
• Manipulated highly-dimensional data for empirical testing of such models
• Automated data engineering tasks through programmatic means in both local and virtualized environments
• Created reports, visualizations, and slideware for executives to summarize findings

• Led a team of presenters and researchers
• Read academic literature relating to network and compute research to provide evaluation of R&D projects
• Lectured daily on specific research areas to large business, government, and education audiences
• Researched justification for nascent technologies (i.e. 5G) and documented findings
• Collaborated with developers, engineers, and architects to understand complex technology
• Managed 50+ technologies in a research facility designed for presenting R&D projects

• Analyzed specific markets to determine product fit for strategic gain
• Evaluated technologies for alignment within specific strategic frameworks
• Compiled attribute data on disparate products to form an effective product portfolio
• Wrote documentation for technical or strategic communications for Verizon executives
• Developed technical demonstrations to communicate functional validity of prototypes

• Investigated opportunities to expand market reach for core product line in a startup environment
• Interviewed market participants to determine viability of a specific R&D project
• Designed, marketed, sold, and deployed a novel managed solution for 3D printing to four US universities (see Projects section below)
• Lectured on the evolution of 3D printing at universities, conferences, and trade shows

• Established an inside SMB sales channel throughout retail locations to grow YoY revenue without hiring additional staff or increasing retail footprint
• Developed outbound strategy based on empirical measures of customer engagement
• Developed inbound strategy to identify SMB customers from consumer retail interactions
• Facilitated events to educate customers and peers on Apple’s SMB strategy and solutions

• Formal education and professional experience with neural networks, algorithmic optimization, frequentist statistics, Bayesian statistics, econometrics, data visualization techniques, ETL, data mining and codification, schema design, modeling and forecasting, and diagnostic and specification testing.

• Formal education and professional experience in the effective presentation, facilitation, documentation, and collaboration of ideas and concepts.

• Extensive, daily experience with R, Python (including Pandas, PyTorch, Keras, Scikit Learn, Numpy, etc), Alteryx / Knime, Tableau, Unix, version control (Github), and database languages (both SQL and noSQL). Extensive experience with PHP, C++ and C#, and compute resources like AWS, Azure, IBM Watson, OpenAI, and GCP. Experience with MATLAB, EViews, and Omnisci.

• Passionate hockey player and golfer. Avid reader of military history, business history, and biographies. Lifelong musician and player of the guitar, piano, and drums.

General reinforcement learning research in finance and economics 2022 - Present

At the PhD program at CU Boulder, develops methods for using Markov Decision Processes (MDPs) and their variants (such as POMDPs) in finance and economics applications such as price prediction, risk management, portfolio management, and general market strength determination.

"The Efficacy of a Regime-Switching Asset Pricing Model Conditioned on Market Volatility" DBA Dissertation, 2023

A proprietary statistical model that explains public equity returns in different market regimes, as defined by general return volatility.

Experiments with Systematic Fundamental Asset Pricing Models Dissertation exploration, 2020

Builds systematic (programmatic) asset pricing and portfolio management models from financial and fundamental data from firms in the US and abroad to determine the effect of firm management on stock returns, and the attributes of those returns. Have started incorporating machine learning methods into these models (GANs, SVMs, etc) to increase the explanatory power and potential predictive capability of these models which can be used in industry for active money managment or in academia to explain systemic factors of return premia. Guofu Zhou from the Finance Department of Washington University in St. Louis advises on some of these activies.

Determining Explanatory Power of Charateristics in Modern Asset Pricing Models Research assistantship, 2019

Working for David Rapach and Ilias Filippou in the Finance Department in the Olin Business School at Washington University in St. Louis by creating dynamic ETL programs in R to collect, clean, structure, and analyze numerous firm characteristics over the universe of stocks in the US - about 29,000 firms.

Dissecting the Specification Effectiveness of Ramsey's RESET Test Research assistantship, 2019

Working for Robert Parks in the Economics Department of Washington University in St. Louis by creating programs in R and EViews that test published results and suggest improved variants of the RESET test.

Bed, Bath, and Beyond: A Valuation Analysis Summer research paper, 2019

Abstract: Bed, Bath, and Beyond, Inc. (“BBBY”) is an omnichannel home décor retailer with 1,552 stores in the US, Canada, and Mexico. Over the last five years, they have been unsuccessful in growing top line revenue (5-year CAGR of 1.8%) while costs have continued to rise (five-year CAGR of 3.3%). While management has adroitly run the operating side of the business as evidenced by healthy financial ratios including higher than industry average ROE (27%), a low debt-equity-ratio (0.4x), and high EBIT interest coverage (18x), BBBY is projected to run out of debt-free cash flows in 2021 due to their evaporating net income. With this information, BBBY is evaluated at a SELL recommendation as its equity is valued at $429M on a DCF basis and $528M on a multiples basis; these are well below the $2.2B the company currently holds in market capitalization.

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“Does Financial Statement Analysis help pick winners from an OTC equity market?” Summer research paper, 2019

A research paper conceived and written in a seven-week period during the last semester of my MBA under advisor Francois Brochet, Associate Professor of Accounting at Boston University.

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