Robert L. Mead II
Data Analyst
ABOUT
A middle school mathematics teacher looking for a career change. Pursuing a Masters in Applied Mathematics with a specialization in Statistics and Data Analytics by developing competencies in modeling, statistics and computations needed to solve real world problems enabled by productive experiences on collaborative projects. Seeking a job in statistics and data analytics.
SKILLS & EXPERTISE
-
Probability and Statistics
-
Differential Equations
-
Linear Algebra
-
Data Cleaning and Data Manipulation
-
Data Analysis
-
Data Visualization
-
Model Deployment
-
Machine Learning
-
Programming Languages:
-
R Studio​
-
Python
-
SQL
-
LaTex
-
Mathematica ​
-
PROJECTS
PHARMACOKINETICS | October 2020 - December 2020
-
Created an exponential regression model of a single intravenous drug dose in a two compartment open model.
-
Identified invariance in data, and used data transformation procedures.
-
Estimated coefficients of an exponential regression model by using a data frame. Exponential peeling procedures were used to estimate the coefficients of each compartment that the drug dose decayed over time.
INSURANCE RISK | June 2021 - August 2021
-
Used a Pareto Distribution to compute analytical statistics for an insurance company.
-
Compared analytical and experimental statistics through simulation.
-
Determined the likelihood of an insurance company going bankrupt under a set of certain parameters.
BITCOIN MODEL | June 2021 - August 2021
-
Analyzed the Bitcoin, BTC, stock indices through time series analysis.
-
Modeled Bitcoin on a stochastic volatility correlated jump model. Determined the impacts jumps have on option prices through simulations, and analyzed implied volatility.
BIOMASS PRODUCTION | November 2021 - December 2021
-
Fitted an ordinary least squares regression to a data frame to identify significant predictor variables.
-
Transformed data, due to invariance, and identified collinearity between predictor variables using standard procedures.
-
Performed a Principle Component Regression, due to the fact that collinearity was prevalent among the predictor variables.
-
Completed a Best Subset Regression based on the Principle Component Regression to identify the significant predictors.
-
Cleaned data frame using median imputation.
-
Used Bayesian Statistical Analysis to identify significant predictor variables.
-
Performed an Ordinary Linear Regression to identify predictor variables.
-
Completed a Posterior Analysis using a Posterior Distribution simulate the coefficient values.
-
Obtained a Posterior Predictive Distribution to make predictions and determine the accuracy of predictions.
PHARMACODYNAMIC CANCER MODELS | January 2022 - June 2022
-
Solved the Gompertz Equation and the Logistic Equation to analyze the affects of tumor growth and vasculature growth.
-
Solved pharmacodynamic equations with continuous dosing and periodic dosing of a chemotherapeutic drug and an anti-angiogenic drug on the tumor and the vasculature.
-
Solved coupled pharmacodynamic models to analyze the affect of the vasculature on the tumor.
-
Analyzed a one-compartment pharmacokinetic model, the Hahnfeldt Model.
-
Solved the Hahnfeldt Model utilizing Mathematica
EDUCATION
2020 - 2022
Illinois Institute of Technology
Masters of Applied Sciences | Applied Mathematics
Chicago, IL
Courses - Mathematical Modeling, Probability, Introduction to Mathematical Finance, Mathematical Statistics, Project Management, Case Studies and Project Design, Advanced Design of Experiments, Applied Statistics, Bayesian Computational Statistics, Masters Project
2013 - 2017
Dominican University
Bachelor of Arts | Mathematics
River Forest, IL
Certified Mathematics Teacher 6th- 12th Grade
​