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Robert L. Underwood

Budding Data Analyst

Biography

WELCOME!

So either you stumbled upon this page or you were directed here. In any case, welcome to the home of Robert Underwood. Obviously, I’m Robert Underwood. Let me tell you a bit about myself.

I was born and raised in Pittsburgh, PA. As class valedictorian at Oliver High School in 2005, I was expected to do great things. Then I graduated with a Bachelor of Science in Mathematical Sciences from Carnegie Mellon University in 2009 into the worst recession seen since the Great Depression.

Not a promising start.

Since then, I’ve bounced around in various fields. In my career, I’ve been a desk attendant, test grader, appraisal and BPO reviewer, customer service representative, and bank teller. I went with being apathetic about politics to a conservative and from being unsaved to a born-again Christian. There have been various tips and tricks that I’ve picked up along the way, some of which I hope to share. Some of those were put to the test as I completed a Master of Science in Analytics from American University.

Now that I am officially a data analyst, I hope to improve my skills to the point where I am a data scientist. I've come a long way from my humble beginnings, but there is a long way to go.

For those seeking knowledge or more information, there are some things that may interest you. Please check out my blog, Ranting Robert.

Interests

  • Data Science
  • Math
  • Statistics
  • Sports

Education

  • MSc in Analytics, 2017

    American University

  • BSc in Mathematical Sciences, 2009

    Carnegie Mellon University

Skills

R

Python

SQL

Microsoft Excel

Statistics

Data Analysis

Data Modeling

Data Visualization including Power BI and Tableau

Experience

 
 
 
 
 

Data Analyst

XLA

Aug 2019 – Present Washington, DC
  • Analyzes complaints submitted through multiple sources, log summaries in Access, and forwards complaints to officers for follow-up action as needed.
  • Researches specific complaints using other internal databases and case logs.
  • Assists in developing and testing new functions to increase productivity and reduce turnaround time.
 
 
 
 
 

Junior Peoplesoft Developer

Fannie Mae

Jun 2018 – Feb 2019 Herndon, VA
  • Updated over 700 test scripts using Peoplesoft Test Framework.
  • Reviewed team interfaces and updated internal database with new interface control documents.
 
 
 
 
 

Data Analyst Trainee

FDM Group

Mar 2018 – May 2018 New York, NY
  • Received additional training in SQL including Oracle SQL and Microsoft SQL Server.
  • Trained and completed projects using SSIS and SSAS.
  • Completed a data visualization project using Power BI to create a sales dashboard.
 
 
 
 
 

Video Banking Teller

Dollar Bank

Sep 2015 – Mar 2018 Pittsburgh, PA
  • Serviced banking needs remotely from customers at 11 locations in three states.
  • Promoted machine functions via branch visits leading to a 75% increase in customer usage.
  • Built and maintained a new schedule template which reduced the time spent completing schedules by 50%.
 
 
 
 
 

Bank Teller

Allegheny Valley Bank

Oct 2014 – Aug 2015 Pittsburgh, PA
  • Serviced various financial concerns from customers and recommended products and services.
 
 
 
 
 

Quality Control Analyst

Servicelink

Apr 2011 – Aug 2013 Moon Township, PA
  • Reviewed broker price opinions and desktop housing appraisals.
  • Exceeded review goals consistently by 50% while maintaining a 97% accuracy rate, resulting in progressive responsibility to review reports from three different clients.
  • Reviewed test reports from a potential client, resulting in the acquisition of the client and a 25% increase in volume.

Academic Projects

Email Marketing Data Group Project

  • Analyzed email marketing data – both company and third-party data – to build a model that could predict email responses while reducing the total emails sent by over 50% and presented to company representatives.
  • Identified 15 variables out of 300 in the third-party dataset that resulted in a response rate outside of the average response rate and cleaned the data to create a new dataset for modeling.
  • Built, trained, and compared various models which were used to identify how many emails would need to be sent to retain 80% of responses.

Predictive Analytics Term Project

  • Identified and transformed variables in infant birth weight dataset in R to build models that could predict infant birth weight and provided suggestions.

AU Personal Care Group Project

  • Created a visual analytics tool in Tableau to identify key salespersons, customers, and products that were useful maximizing revenue and recommended the discontinuation of low-performing products
  • Summarized sales patterns and reported outlying high-performance month

Projects

Low Birth Weights

A brief analysis of the birth weight dataset in R

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