Mark Comstock Email & Phone Number

I’m a graduate of the University of Wisconsin-Madison with a Bachelors degree in Actuarial Science. Go Badge! At UW-Madison, I developed a passion for mathematics, statistics, coding, data analytics, and finance. I'm currently a Forecasting - Senior Actuarial Analyst at Centene Corporation. I've been with Centene for over 4 years now (3+ years full time after starting there as an intern).Currently the owner of forecast insights for eight states: evaluating forecast reasonability, seasonality, member mix drivers, forecast adjustments, state-specific developments, etc. I'll collaborate quarterly with pricing state leads, providing insightful forecast narratives about their state in effort to strengthen confidence about their price position and states current standing.I lead over 5 different processes during our month close process which is essentially telling the story of what happened in a given month, and in our case, how claims are coming in. Those processes include: Lag Commentary Model, Rx GPI Model, Covid reporting, State-Specific Variance to Forecast Model, Net of Covid Plots, and other Ad-Hoc projects.I've built multiple applications using R-Shiny to showcase Episodic Treatment Group (i.e. Malignant Neoplasm, Heart Disease, Chronic Renal Failure), Medical Practice Category (i.e. Cancer, Cardiology, Nephrology), and a Pharmacy-GPI (i.e. Antivirals, Obesity Drugs) dashboard to evaluate outliers and trends on a monthly basis. Also, I’ve built another R-shiny model hosting multiple time series models which are excelling at predicting our future medical and pharmacy claims.I'm the owner of our Pharmacy Forecast (brand Rx claims, generic Rx claims, specialty Rx claims, and rebates) in our Annual Operating Plan and Quarterly Forecast cycles and our Medical/Rx Unit Cost & Utilization Trend component in our Annual Operating Plan (AOP).Taken an interest in machine learning projects specifically using the tidy-models framework in R. I've utilized XGBoost, Random Forest, Support Vector Machines, etc. to predict claims alongside of time-series work. Have also utilized machine learning models to build stock market and National Football League algorithms as hobbies.Exams Passed (5) - Financial Mathematics, Probability, Investment and Financial Markets, Statistics for Risk Modeling, Predictive Analytics.Program Knowledge and Technical skills: Excel (VBA), R-Studio, R-Shiny, R-Markdown, SQL, Machine Learning Algorithms (XGBoost, Random Forest, etc.), Time-Series, Tidy-models, HTML, Power BI, and some Python.

Listed skills include Leadership, Python, Microsoft Word, Microsoft Sql Server, and 12 others.

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  University Of Wisconsin-Madison

  Actuarial Science