Michael Leon Chrzan

Data Scientist bridging K12 education practice, policy, and advanced analytics through machine learning, causal inference, and NLP to drive educational equity and evidence-based improvement at scale.

Data Science for Education Impact

I partner with school districts, education nonprofits, and EdTech organizations to translate complex data challenges into actionable insights that drive equitable outcomes. With over a decade bridging K-12 education practice and advanced analytics, I bring both deep domain expertise and technical rigor to every engagement.

What I Offer

Strategic Data Analysis & Research

  • Predictive modeling for enrollment forecasting, student outcomes, and resource optimization
  • Machine learning applications for early warning systems and intervention targeting
  • Natural language processing for analyzing qualitative feedback, surveys, and community input
  • Causal inference studies to evaluate program effectiveness and policy impacts

Education Policy & Planning Support

  • Evidence-based decision support for district leadership and policy teams
  • Data protocol development for instructional leadership and continuous improvement
  • School closure scenario analysis with equity-centered metrics and community impact modeling
  • Resource allocation optimization using data-driven frameworks

Tool Development & Technical Solutions

  • Custom Python packages for measurement, analysis, and data processing
  • R package development for education finance and longitudinal data analysis
  • Dashboard and visualization systems for stakeholder communication
  • Data pipeline automation to streamline reporting and analytics workflows

Why Work With Me

Deep Education Expertise — Ten years as a classroom teacher and Math Master Teacher means I understand the realities of schools, not just the data. I’ve mentored 20+ teaching interns, led instructional teams, and driven measurable improvements in student outcomes.

Technical Excellence — Stanford M.S. in Education Data Science (4.1 GPA, Dean’s Fellow) with specialization in causal methods, machine learning, NLP, and measurement. Published research and active contributor to open-source tools.

Equity-Centered Approach — My work prioritizes historically underserved communities. I develop metrics uncorrelated with historical inequities and design analyses that surface rather than obscure equity concerns.

Practical Impact — I focus on delivering actionable insights, not just reports. Whether it’s early warning systems, policy simulations, or analysis tools, my work is designed to support real decisions and drive meaningful change.

Current Focus Areas

  • AI applications for educational equity
  • School closure and consolidation modeling
  • Evidence-based policy evaluation
  • Ethical AI implementation in education settings
  • Large-scale administrative data analysis
  • Community feedback and stakeholder engagement analysis

Select Client Work

Bellwether Education Partners — Contributed to the development of edfinr, an open-source R package supporting education finance data analysis and visualization for researchers and policymakers nationwide.

San Francisco Unified School District — Built a comprehensive scenario generation algorithm evaluating 400+ viable school closure options with equity-focused quality indicators, enabling data-informed decision-making that minimized harm to vulnerable communities.

National Summer School Academies — Designed and implemented data processing workflows to support program evaluation and continuous improvement across multiple sites.

Let’s Talk

Whether you’re facing a specific data challenge, planning a complex policy decision, or looking to build internal analytics capacity, I’d be happy to discuss how I can help.

Contact: mlchrzan1@gmail.com
LinkedIn: linkedin.com/in/mlchrzan

Currently accepting select consulting engagements while maintaining my role as Data Scientist at the Center for Educational Data Science and Innovation (EDSI).