Max Ghenis
Summary
Policy entrepreneur, technologist, and economist building computational tools that democratize policy analysis. Founder of PolicyEngine, a nonprofit software platform that computes personalized and population-level impacts of tax and benefit reforms. Expert in microsimulation modeling, machine learning for survey data enhancement, and economic impact assessment.
Professional Experience
October 2021 - Present
- Founded and currently lead PolicyEngine, a nonprofit software platform enabling policymakers, researchers, and citizens to analyze personalized and population-level impacts of tax and benefit policy reforms in the US and UK
- Built comprehensive tax and benefit microsimulation models covering federal and state income taxes, payroll taxes, capital gains, VAT, and major benefit programs including Medicaid, CHIP, ACA subsidies, SNAP, SSI, TANF, Universal Credit, Child Tax Credit, and Social Security/State Pension benefit taxation
- Serve diverse users including government agencies (Joint Economic Committee, DC Council, NY Senate), research organizations (NBER), universities (Georgetown, University of Michigan), think tanks (Niskanen Center, Arnold Ventures), and advocacy organizations
- Launched PolicyEngine UK in October 2021; launched PolicyEngine US in 2022 with all 50 states and federal programs
- Secured and delivered grants, research contracts, and API service agreements with partners including Federal Reserve Bank of Atlanta, NBER, National Science Foundation ($300K), NEO Philanthropy ($200K), and Nuffield Foundation (£250K)
- Enhanced microsimulation accuracy using machine learning for variable imputation and survey weight calibration, reducing deviations from administrative statistics by 97%
Founder and President, UBI Center
April 2019 - March 2023
- Created an open source think tank conducting quantitative research into universal basic income and cash transfer policies
- Managed team of up to a dozen researchers, collectively producing over 60 reports and interactive analytical products
- Developed open-source tools for distributional policy analysis, including microdf Python library for weighted survey data analysis
- Published research influencing policy debates on child allowances, carbon dividends, and tax reform
Independent Economics Researcher
July 2018 - March 2019
- Produced a synthetic releasable version of the IRS Public Use File for open-source tax analysis as part of the Open Source Policy Center’s Tax-Calculator project (Python)
- Contributed to Tax-Calculator’s imputation of variables from Current Population Survey to IRS data sets
- Conducted distributional analysis of federal cash transfer policies including EITC, CTC, and UBI (Python+Jupyter)
Product Analyst / Data Scientist, YouTube
July 2015 - July 2018
- Led analytics for emerging markets and YouTube Go—an app for low-bandwidth users—including modeling user retention, designing and analyzing experiments and quasiexperiments, and advising on data infrastructure
- Associated geographic consumption of video segments with economic indicators
- Built tool for automatically estimating causal impact of mobile data discount campaigns on YouTube consumption using Bayesian time series
- Developed and productionized classification of 100M+ content creators using PCA and LASSO
- Built forecast model for daily reach for thousands of slices using hierarchical time series
- Conducted first deep-dive analysis of female YouTube usage
- Led quantitative analysis for algorithm estimating reach across videos, channels, and countries
People Analytics Manager, Google
July 2010 - July 2015
- Promoted twice (People Analyst → Senior People Analyst → People Analytics Manager), co-founding People Analytics Data Science team and establishing data-driven approaches to workforce planning and organizational effectiveness
- Led social network analysis of company-wide survey, including force-directed graph layouts, predictors of employee PageRank centrality and edge formation, and organizational integration
- Conceptualized and executed restructure of People Analytics survey data, leveraging internal SQL and writing functions in custom R package for consistent, efficient, longitudinal analysis
- Analyzed promotion and transfer activity via survival analysis and random forests
- Created automatic headcount forecast using R Monte Carlo simulation, chaining ARIMA, Cox survival models, and random forests
- Built R package for topic modeling and sentiment analysis, applied to 15+ domains and 350k+ documents
- Identified interviewers and hiring stages most predictive of hiring and performance outcomes
- Created original educational content for Sheets, R, and SQL; delivered 200+ hours of teaching to hundreds of employees; held YouTube lectures for G Suite and Google’s data analysis MOOC
June 2008 - July 2010
- Promoted from Analyst to Senior Analyst during tenure
- Consulted for pharmaceutical companies on sales force optimization, territory alignment, and resource allocation
- Developed predictive models for sales forecasting and market analysis
Education
M.S., Data, Economics, and Development Policy | 2020
Massachusetts Institute of Technology
B.A., Operations Research and Management Science | 2008
University of California, Berkeley
Minors: Industrial Engineering & Operations Research, Music
Key Skills & Technologies
Programming & Data Science:
- Expert: Python (pandas, NumPy, scikit-learn), R (ggplot2, tidyverse), SQL, Jupyter
- Proficient: JavaScript/TypeScript, React, Stata, Google Apps Script, Linux/shell
- Intermediate: SAS, VBA
AI & Modern Development:
- LLM programming and prompt engineering
- AI coding agents (Claude Code, GitHub Copilot)
- Automated code generation and testing
Specialized Expertise:
- Microsimulation modeling and agent-based simulation
- Machine learning for survey data imputation and calibration
- Tax and benefit policy analysis
- Distributional economic impact assessment
- Causal inference and experimental design
- Data visualization and interactive tools
- Open-source software development
Domain Knowledge:
- Tax policy design and reform analysis (income, payroll, wealth, carbon taxation)
- Social insurance programs and benefit-cliff analysis
- Universal basic income and cash transfer policies
- Survey methodology, synthetic data generation, and statistical matching
- Poverty and inequality measurement (SPM, deep poverty, distributional analysis)
Selected Publications & Research
Working Papers
Book Chapters
PolicyEngine Research
Substack
UBI Center Research
Conference Presentations & Speaking Engagements
National Tax Association (NTA) 117th Annual Conference on Taxation | November 2024, Detroit, MI
- “What Can LLMs Tell Us about the ETI?” With Jason DeBacker
- “PolicyEngine’s Enhanced Current Population Survey for Tax-Benefit Microsimulation.” With Nikhil Woodruff
Association for Public Policy Analysis and Management (APPAM) Fall Research Conference | November 2024
National Tax Association Spring Symposium | 2024
BenCon | 2024
Open Sustainability Summit | 2024
Rules as Code Europe | March 2025, Paris, France
Society of Government Economists (SGE) Annual Conference | Washington, DC
University Guest Lectures | 2024
- UC Berkeley
- Northwestern University
- George Mason University
- University of Toronto
Rules as Code Demo Day, Beeck Center | June 2022, Washington, DC
- Presented PolicyEngine platform with Nikhil Woodruff
Basic Income Guarantee (BIG) Conference | June 2022, Portland, OR
Professional Affiliations & Advisory Roles
September 2020 - Present
- Lead organization supporting open source products for public policy analysis
Synthetic Data Advisory Board Member, Tax Policy Center
August 2019 - Present
- Advise on development of synthetic version of IRS Public Use File for accurate, privacy-safe policy analysis