Rebecca Frost-Brewer

Rebecca Frost-Brewer

Data Scientist

Welcome!

I’m glad you’re here. I am a data scientist, obsessed with solving challenging problems by exploring and analyzing large datasets. For six years, I worked in higher education where I conducted analysis of internal datasets to extract insights to drive program and service decision-making. Further, I defined measures of success, developed and communicated both findings and recommendations to non-technical audiences, and built self-service tools for ongoing monitoring of trends.

While my professional experience as a data scientist may be limited, I am well-versed in the technical programs and languages (Python / R) necessary to meet the expectations of all job responsibilities. I am excited by the challenge of solving problems using a wide array of modeling and quantitative techniques; my portfolio includes projects using multiple linear regression, logistic regression, decision trees and random forest classifiers, and ensemble methods like XGBoost.

I am deeply curious and comfortable solving unstructured business problems by exploring large datasets and keen to deliver meaningful insights and predictions about emerging trends to inform business solutions. I am obsessed with asking questions, researching, problem-solving, and presenting my findings.

I look forward to every opportunity to demonstrate my proficiency as a data scientist.

Download my résumé.

Education

  • Data Science, 2022

    Flatiron School

  • MA in Political Science, 2021

    Georgia State University

Projects

Decision Tree Tuning
GridsearchCV - Example
Logistic Regression Example: Predicting Forest Cover Type
Nonparametric Machine Learning Model Example
Machine Learning Theory and Fundamentals
A-B Testing Lab
Hypothesis Testing Codethrough
Linear Regression Analysis
Preprocessing Data with Scikit-Learn
Using Exploratory Data Analysis to Generate Insights for a Business Stakeholder
Using Multiple Linear Regression for Housing Sale Price Analysis
SQL Demonstration
Data Exploration with Pandas
Working with Different Data Structures
Data Visualization Using Bump Charts and Line Plots with `ggplot`
Data Visualizing using R and `ggplot2`

Recent Posts

Intro Codethrough to Machine Learning Classification Algorithms

This post will be a simple, surface-level walk-through of some of the key components of machine learning classification algorithms.
Last updated on May 31, 2022 6 min read
Tip-Toeing Into Machine Learning
Eight weeks into the Flatiron School’s Data Science program, I stand on the precipice of my foray into machine learning. Thus far, I’ve been introduced to Jupyter notebooks, Python, pandas, Matplotlib, NumPy, SciPy, and statsmodels.
Last updated on Apr 23, 2022 4 min read
Manifesting a New Direction
After six years working in higher education administration and the successful completion of a Master’s degree in Political Science, I am changing careers into data science and analytics. As I reflect back on my professional life to date, it’s characterized by a lack of intentionality, a lack of purpose.
Last updated on Mar 20, 2022 5 min read

Skills

R

tidyverse, ggplot2

Python

pandas, matplotlib, NumPy, SciPy, scikit-learn

SQL

Experience

 
 
 
 
 
Solving a Classification Problem
Flatiron School
May 2022 – Present

Tasks included:

  • Apply appropriate preprocessing and feature engineering steps in preparation for predictive modeling
  • Demonstrate iterative approach to modeling, building different kind of models (decision trees, random forests, k-nearest neighbors, XGBoost), tuning hyperparameters, and assessing classification metrics (F1-scores)
 
 
 
 
 
Multiple Linear Regression
Flatiron School
Apr 2022 – Present

Tasks included:

  • Identify the appropriate modeling technique given a problem statement based on the availability, variety, and quality of data
  • Build a baseline linear regression model as well as several iterative models, and extract insights from a final multiple linear regression model to make business recommendations
  • Communicate regression results of statistical analyses to diverse audience via writing and oral presentation
 
 
 
 
 
Accommodation Support Specialist
SCAD
Jan 2019 – Sep 2021

Responsibilities included:

  • Data collection and exploratory data analysis to find trends in client needs, satisfaction, and outcomes
  • Assess effectiveness of services and resources across multiple divisions and business units
  • Build and maintain summary statistics for reporting and tracking purposes
 
 
 
 
 
Assistant Director, Disability Services
Georgia Institute of Technology
Oct 2017 – Jan 2019

Responsibilities included:

  • Track and manage client data for completion and accuracy
  • Write reports and presenting educational information and recommendations related to service implementation
  • Communicate with staff and stakeholders to understand service implementation
 
 
 
 
 
Director, Academic Support Services
Whitman College
Jun 2015 – May 2017
Oversee early intervention programs, track student degree progress using analytics. Manage three office budgets, retain gift funding, and write analytics reports. Establish and assess outcomes to inform evidence-based best practices.