Machine Learning Data Science

Mark E Pierson

Data Scientist

*******.******@*****.*** • 214-***-****

LinkedIn • Austin, TX 78717

Strategic and results-driven professional with extensive experience in delivering advanced analytics, predictive modeling, and data-driven insights across healthcare, education, and public health domains. Proven track record of deploying machine learning models to optimize healthcare outcomes, including reducing inpatient visits and emergency room utilization. Expert in developing propensity score models, statistical testing (e.g., ANOVA, t-tests, regression), and automating reporting pipelines using R and Python. Adept at translating complex data into actionable intelligence for stakeholders, with a focus on improving population health, operational efficiency, and strategic decision-making. Strong collaborator with cross-functional teams, experienced in BI tools such as Tableau, Power BI, and SSRS, and proficient in SQL-based data engineering for ETL processes. Recognized for bridging the gap between statistical rigor and business value in corporate and research settings. Areas of Expertise

● Machine Learning

● Statistical Analysis

● Predictive Modeling

● Data Visualization

● ETL & Data Pipelines

● Machine Learning

● Research & Reporting

● Statistical Programming

● SQL & Database Querying

Professional Experience

Centene Corporation, Austin, TX

Biostatistician III

March 2018 — November 2024

Addressed diverse data requests from federal, state, and internal business partners, ensuring accurate and timely responses. Developed propensity score models matched on medical and demographic variables to evaluate healthcare outcomes between treatment and control groups. Predicted member rehabilitation needs to reduce emergency room visits through advanced data analysis. Deployed machine learning models that effectively reduced inpatient visits for members with substance use disorders, showcasing data-driven approach to healthcare optimization.

●Acted as Centene Data Science R User Group (CRUG) liaison with RStudio (now Posit), facilitating integration of new tools and methodologies.

●Automated high-impact reporting pipelines using R and Python, enhancing both report delivery speed and accuracy.

●Conducted statistical testing using Pearson & Spearman correlations, t-tests, Mann-Whitney U, ANOVA, and Kruskal-Wallis tests to evaluate group differences and relationships.

●Developed predictive models via multiple linear, logistic, and stepwise regression to identify key drivers and forecast outcomes.

●Utilized advanced analytics techniques including CART (Classification and Regression Trees) and K-means clustering for pattern recognition and segmentation.

Hanger, Inc., Austin, TX

SSIS / ETL - Data Analyst

September 2017 — March 2018

Leveraged Microsoft Visual Studio and SSRS to create and maintain reports and dashboards. Collaborated with data management team to design an effective inventory valuation system. Developed and implemented SQL agent jobs to capture time-sensitive information accurately. Engaged in writing stored procedures to efficiently organize, manipulate, and evaluate large datasets. Conducted data validation to ensure integrity and accuracy across analytics processes.

●Developed a reporting suite with key performance indicators that automatically refreshed daily.

●Presented report results to management, aiding in resource allocation and strategic decision-making. TAV Health, Austin, TX

Data Analyst

January 2017 — September 2017

Conducted in-depth analysis of Protected Health Information (PHI) to derive meaningful insights. Crafted and maintained reports from raw datasets, ensuring clarity and usability. Executed cross-sectional correlation analyses to uncover relationships between health barriers and solutions. Transformed data across relational databases, including patient episodes and associated activities. Employed Linear Regression models to forecast social determinants impacting health and reducing hospital readmission rates. Collaborated with cross-functional teams to optimize data processes and enhance healthcare outcomes.

●Visualized complex datasets using business intelligence tools such as Tableau to improve decision-making processes. Page 1 2

●Developed models of social determinants of health to link patients with critical resources, such as food shelters and clinics. Johns Hopkins University, School of Education, Baltimore, MD Senior Research Associate – Data Analyst

January 2014 — December 2016

Executed data analysis on educational datasets across school, district, state, and federal levels, ensuring insights into performance metrics. Imported, cleaned, merged, and manipulated substantially large datasets to form coherent formats for analysis. Calculated and structured data for tabular and graphical presentations to facilitate understanding. Summarized relevant literature and methodologies to support research conclusions. Utilized ArcGIS to graphically represent data over geographical regions. Compiled and synthesized data for annual reporting, while delivering univariate and multivariate statistical analysis results with tools like SPSS and STATA.

●Graphed educational performance across geographic areas to identify regions of varying educational outcomes.

●Projected student metrics for improving test scores and graduation rates to enhance community social health. Additional Experience

Business Analyst III / Business Analyst II, Superior HealthPlan, Austin, TX Research Associate, Johns Hopkins University – Bloomberg School of Public Health, Department of Mental Health, Baltimore, MD Research & Retention Graduate Assistant, Loyola University Maryland – ALANA Services, Baltimore, MD Project Evaluation Assistant – Data Analyst, Office of Minority Health (OMH), Denton, TX Office Manager Research Assistant, University of North Texas – Center for Psychosocial Health Research (CPHR), Denton, TX Education

Master of Science (MS) Statistical Methods & Research Methodology Loyola University Maryland, Baltimore, MD

Bachelor of Science (BS), Cum Laude Psychology

University of North Texas, Denton, TX

Associate of Arts (AA)

Collin College, Frisco, TX

Technical Proficiencies

R (v4.2.2 – Pile of Leaves) RStudio JupyterHub SQL STATA SPSS Mplus Data Scientist (SCI) ArcGIS Tableau Power BI MicroStrategy SSMS SSRS Visual Studio Microsoft Office Suite Publications

Pierson, M. E., Prenoveau, J. M., Craske, M. G., Netsi, E., & Stein, A. (2017). Psychometric Properties of the Generalized Anxiety Disorder Questionnaire - IV (GAD-Q-IV) in Postpartum Mothers. Psychological Assessment. http://dx.doi.org/10.1037/pas0000443

Iwasaki, M., Pierson, M. E., Madison, D., & McCurry, S. M. (2015). Long-term care planning and preferences among Japanese American baby boomers: Comparison to non-Japanese Americans. Geriatrics & Gerontology International. http://dx.doi.org/10.1111/ggi.12601

Pierson, M. E., & Prenoveau, J. M. (2015). Two-factor theory of avoidance learning. In R. McCabe & I. Milosevic (Eds.), Phobias: The Psychology of Irrational Fear. Santa Barbara, CA: ABC-CLIO. Page 2 2

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