Senior Policy Lead

Chuanyu Mu

**** ******* **. **** ****, Fairfax, VA, 22030, 202-***-****, ***********@*****.***

EXPERIENCE

The SPHERE Institute - Washington, DC

Senior Policy Lead (Promoted from Data and Policy Analyst I) Mar 2017 – Present

Led data-driven initiatives by leveraging descriptive and inferential statistics to extract insights and provide recommendations to clients. Identify data quality issues, then design and implement solutions for large-scale data management and manipulation using Python, Apache Spark, SQL, SAS, and STATA.

Managed end-to-end project lifecycles, including defining research scope, estimating budgets and timelines, developing methodologies and algorithms, collecting and cleaning data, ensuring quality control, and delivering findings to stakeholders.

Mentored and trained junior team members in data analysis, programming, and healthcare policy, fostering a collaborative environment that drove professional growth. Successfully managed 10+ direct reports, with many receiving promotions. Example Projects:

Provider Entity Type Prediction Model

o Developed a random forest model in Python to predict Medicaid-enrolled provider entity types (individual vs. organizational) with 95%+ accuracy.

o Improved model performance by 30% through extensive data cleaning, feature engineering, and data correction.

Medicare and Medicaid Summary Files (Monthly and Annually) o Managed 80TB data using Apache Spark, developed Python-based data pipelines that optimize data processing and reduced computation time by 90%.

o Produced structured research files summarizing U.S. population demographics, health conditions, healthcare utilization, and spending, aiding leadership in developing business proposals. o Delivered key insights and data product to clients, contributing to publications by Medicaid and CHIP Payment and Access Commission (MACPAC) and Medicare Payment Advisory Commission (MedPAC).

Opioid Prescribing Fraud Detection

o Analyzed over 40TB of Medicaid claims data in PySpark and SAS to identify fraudulent opioid prescribing patterns. o Utilized clustering techniques to detect prescription outliers and quantified their impact on health outcomes. o Created data visualizations in Python, delivered actionable insights to the Center for Program Integrity (CPI), leading to continued collaboration with state Medicaid agencies on fraud detection and policy regulation.

Impact of Dobbs v Jackson Ruling on Male Vasectomy Rates o Led a team of 3 analysts in analyzing shifts in male vasectomy rates post-ruling using Medicaid data. o Automated Python workflows for repeatable analysis, handling missing values, outliers, and feature engineering. o Applied statistical methods to conduct a two-sample t-test, assessing the direct impact of the policy change on vasectomy rates, stratified by socioeconomic status.

o Delivered findings and data visualizations (using Matplotlib and Seaborn) to ASPE clients, contributing to public reports and sparking broader discussions on the policy’s implications.

Behavioral Health Conditions Analysis

o Led a team of 4 analysts in analyzing the U.S. Medicaid population with behavioral health conditions. o Developed a robust methodology to identify the study population, minimizing false positives and ensuring data integrity. o Performed multi-dimensional data analysis of healthcare spending and utilization across disease cohorts, stratified by socioeconomic status, using Python and SAS, incorporating cross-validation techniques to ensure quality results. o Delivered insights to MACPAC and Congress, directly influencing Medicaid policy improvements.

Telehealth Utilization During COVID-19

o Directed a team of 5 analysts in analyzing Medicaid telehealth usage trends before and after COVID-19 using PySpark. o Conducted multimodal data analysis to identify enrollees and providers with the highest increase in telehealth utilization. o Developed a streamlined validation process to ensure the quality of 20+ deliverables within a tight two-month turnaround. o Presented findings to the Office of the Assistant Secretary for Planning and Evaluation (ASPE), leading to published reports and policy recommendations on Medicaid telehealth. National Community Pharmacists Association – Alexandria, VA Healthcare Economics Research Intern May 2016 – Dec 2016

Analyzed prescription drug reimbursement and cost data across 50 states to enhance financial management and market competitiveness for independent pharmacists. Published descriptive statistics and visualizations in the NCPA 2016 Digest.

Managed and updated in-house database using public CMS data on Medicaid prescription pricing using Excel and EViews. University of Science and Technology of China – Hefei, China Pricing Model Research Assistant Sep 2014 – May 2015

Developed a pricing model for fixed-income securities using Monte Carlo simulations and partial differential equations, optimizing trading strategies based on interest rate predictions, implemented in C language. EDUCATION

MIT Professional Education – Applied Data Science Program 2025 (Remote) George Washington University – M.S. in Statistics (GPA: 3.93) Sep 2015 – Dec 2016 Washington, D.C.

GWU Graduate Award (Top 3%) Semi-Finalist, New Venture Competition University of Science and Technology of China – B.S. in Applied Physics (GPA: 3.41) Aug 2011 – Jun 2015 Hefei, China

Outstanding Undergraduate Student of Anhui Province (Top 3%) Leadership Scholarship SKILLS: Proficient in Python, SQL, PySpark, Apache Spark, SAS, and Microsoft Excel. Familiar with STATA, PyTorch, C ACKNOWLEDGEMENT: MedPAC MACPAC Dually Eligible Data Book, January 2024 February 2023 February 2022

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