Michael S. Czahor
Summary
Sports quantitative analyst turned founder & CTO-level leader with 10+ years in data science, AI/ML, and cloud deployment. PhD-trained statistician with executive experience across MLB front offices, enterprise AI systems, and EdTech innovation. Expert in Bayesian modeling, survival analysis, NLP, MLOps, and GCP/AWS architecture, with a proven record of scaling teams, building production systems, and driving data-driven decision making at the highest levels of pro sports and enterprise.
Overview
12
12
years of professional experience
Work History
Special Assistant, Research & Development
Miami Marlins
03.2024 - Current
- Lead development of player health & injury forecasting models.
- Oversaw department hiring and restructured R&D analyst pipeline.
- Mentor senior/junior analysts, elevating technical rigor across the department.
Founder & President / Head of Data Science
AthlyticZ
09.2023 - Current
- Built a custom LMS/CMS platform using Node.js, React, and GCP, serving thousands of learners.
- Scaled 10+ asynchronous programs in Bayesian modeling, Python/ML, and Shiny development.
- Oversaw cloud infrastructure & AI curriculum, securing university and enterprise partnerships.
- Spearheaded fundraising, marketing strategy, and technical roadmap (now in 17 countries).
Principal Quantitative Analyst
Detroit Tigers
05.2023 - 11.2023
- Designed and deployed Bayesian player projection models, directly influencing BB Ops decisions.
- Guided analysts on cloud migration and ML adoption across multiple pipelines.
- Evaluated and implemented emerging AI/ML techniques to modernize modeling infrastructure.
Lead Quantitative Analyst: Integrative Performance
Philadelphia Phillies
01.2018 - 12.2022
- Oversee a cross-functional team of analysts, biomechanists, and engineers to improve player health.
- Launched production dashboards used daily by medical staff to personalize player development.
- Collaborated with scouting, and front office to integrate biomechanics into decision systems.
- Earned Phillies’ Charity Award for mental health program contributions.
Research Assistant & Reliability Engineer
Iowa State University / Fraunhofer IWES
08.2013 - 05.2018
- Developed predictive maintenance software for wind turbines using Bayesian reliability models.
- Built hierarchical models for competing risks and repairable systems with dynamic covariates.
- Collaborated with Northern Power Systems and Fraunhofer IWES on applied reliability projects.
Education
Dual PhD - Statistics & Wind Turbine Engineering
Iowa State University
05-2018
Master of Science - Statistics
Iowa State University
05-2016
Bachelor of Arts - Mathematics
Rowan University
05-2013
Skills
- AI/ML: Bayesian inference, neural networks, NLP, uplift modeling, causal inference, ensemble methods
- Cloud & Infra: GCP, AWS, Docker, Airflow, BigQuery, Nodejs, React, React Native, CI/CD pipelines
- Data Science Tools: Python, R, Stan, PyMC, SQL, Tableau, PowerBI, JAGS
- Leadership: Executive team management, cross-functional collaboration, funding strategy, mentorship
- Domains: Sports analytics, player health modeling, reliability engineering, business automation
Accomplishments
- NSF Grant Member – ESPN’s SCORE Program (2021)
- Invited Presenter – Phillies Medical Symposium (2020)
- Invited Panel Member – UN Paris Climate Negotiations (2015)
References
References available upon request.
Timeline
Special Assistant, Research & Development
Miami Marlins
03.2024 - Current
Founder & President / Head of Data Science
AthlyticZ
09.2023 - Current
Principal Quantitative Analyst
Detroit Tigers
05.2023 - 11.2023
Lead Quantitative Analyst: Integrative Performance
Philadelphia Phillies
01.2018 - 12.2022
Research Assistant & Reliability Engineer
Iowa State University / Fraunhofer IWES
08.2013 - 05.2018
Dual PhD - Statistics & Wind Turbine Engineering
Iowa State University
Master of Science - Statistics
Iowa State University
Bachelor of Arts - Mathematics
Rowan University
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MELISSA ELUIKMELISSA ELUIK
<ul> <li>Advanced equitable forecasting and fund allocation processes to align with university policies.</li> <li>Analyzed budget trends and discrepancies to enhance efficiency in research and special project funding.</li> <li>Conducted participatory data collection to inform transparent financial reporting.</li> <li>Mentored Departmental Assistant and work-study students to build collaborative skills.</li> <li>Facilitated inclusive hiring processes, emphasizing equity in recruitment practices.</li> </ul> at Toronto Metropolitan University<ul> <li>Advanced equitable forecasting and fund allocation processes to align with university policies.</li> <li>Analyzed budget trends and discrepancies to enhance efficiency in research and special project funding.</li> <li>Conducted participatory data collection to inform transparent financial reporting.</li> <li>Mentored Departmental Assistant and work-study students to build collaborative skills.</li> <li>Facilitated inclusive hiring processes, emphasizing equity in recruitment practices.</li> </ul> at Toronto Metropolitan University