Experience

Current Roles:

Silver Bulletin — Assistant Sports Analyst

Remote · 2024–Present

I help build and interpret large-scale NFL, NBA, and NCAA models for Silver Bulletin and turn that work into clear, public-facing analysis.

Burning Glass Institute — Research Assistant

Remote · 2025–Present

I work on labor-market analytics with Dr. Gad Levanon, building data-driven analyses of jobs, skills, and automation for the Labor Matters newsletter and research projects.

Mexico City Capitanes — Basketball Analytics Associate

NBA G League · 2024–Present

I develop metrics and tools for the Mexico City Capitanes to support scouting, roster building, and game-planning under real-world budget constraints.

Past Roles:

Fannie Mae — Data Science Intern

Washington, D.C. · Summer 2025

I worked on income prediction and credit-risk analytics, exploring secondary credit-report features and documenting new data sources for modeling.

Kiva.org — Data Science Co-op, Product Analytics

Remote · Spring 2025

I worked on analytics for MyKiva badges, analyzing churn and engagement across user cohorts and helping shape product experiments and dashboards.

Wakefern Food Corporation — Data Engineer Intern

Edison, NJ · Summer 2024

I built SQL-based stored procedures and SAPUI5/Node.js apps to pipeline store-terminal data into DB2 and automate HR, payroll, finance, and supply-chain workflows.

Scarlet Computing Solutions — Data Science Intern

New Brunswick, NJ · Spring 2024

I visualized OCR model performance with Matplotlib and Plotly, highlighting accuracy improvements and trends through dynamic dashboards.

Wakefern Food Corporation — Software Engineer Intern

Edison, NJ · Summer 2023

I built a real-time React/Node dashboard for Wakefern’s pilot automated store and designed churn and retention metrics to evaluate the store’s first-year performance.

New Jersey Economic Development Authority

NJ Economic Development Authority — Data Analyst Intern

Trenton, NJ · Summer 2022

I analyzed tax-credit and small-business data, building Python pipelines and Tableau maps to support economic development decisions.

Technical Skills:

Programming & Scripting

Python (pandas, NumPy, SciPy), R (tidyverse, ggplot2), SQL, JavaScript, Java, C, Unix shell.

Statistical Modeling & Inference

Linear/logistic regression, GLMs, mixed models, time series, experimental analysis, Elo-style models.

Machine Learning & Forecasting

scikit-learn pipelines, supervised learning, cross-validation, model calibration, forecasting.

Data Engineering & Data Tools

ETL pipelines, DB2, PostgreSQL, Snowflake-style warehousing, schema design, data quality checks.

Visualization & Dashboards

Matplotlib, Plotly, ggplot2, Datawrapper, React dashboards.

Web Scraping, APIs & Automation

requests, BeautifulSoup, ScraperAPI, REST/JSON, robust scraping pipelines.

Workflow, Dev Tools & Collaboration

Git/GitHub, Jupyter, VS Code, reproducible analysis, code review.

Selected Coursework:

Statistics I

Intro probability, estimation, hypothesis testing.

Statistics II

Multiple regression, ANOVA, applied modeling.

Theory of Probability

Random variables, distributions, convergence.

Time Series Modeling

ARIMA, forecasting, diagnostics.

Econometrics

Causal inference, panel data, endogeneity.

Regression Methods

Diagnostics, variable selection, prediction.

Bayesian Data Analysis

Priors/posteriors, MCMC, model comparison.

Machine Learning Principles

Regression, perceptron, logistic regression, LDA/GDA, trees, SVMs, PCA, MLE/MAP, CNNs, Bayesian nets, GMM/EM, VAEs, RBMs, RL, Monte Carlo methods.

Introduction to Data Science

EDA, visualization, kernel density, text/regex, SVD/PCA, supervised learning, deep learning, recommenders.

Data Mining

Clustering, entropy, trees, rules, anomaly detection.

Choice and Strategy in Politics

Game theory, Nash equilibrium, voting rules, coalitions, electoral competition, incentives & institutions.

Business Decision Analysis

Decision trees, probability, sensitivity analysis.

Discrete Structures I & II

Logic, sets, induction, graphs, combinatorics.

Calculus III

Multivariable calculus, gradients, integrals.

Linear Algebra

Vector spaces, eigenvalues, least squares.

Linear Optimization

LP, duality, Simplex, network flow.

Data Structures

Lists, trees, hash tables, asymptotics.

Algorithms

Divide-and-conquer, greedy, DP.

Systems Programming

C, memory, processes.

Computer Architecture

ISAs, pipelines, caching.

Business Data Management

SQL, schemas, normalization.

Creative Writing

Narrative clarity, voice, revision.