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Pete Melgren

Pete Melgren

Data Science Developer

Former data scientist for the Cincinnati Reds.

Pete Melgren is a data scientist with seven years of experience working on end-to-end predictive analytics projects. He has consulted with cross-industry clients on the use of data science concepts such as machine learning, data mining, business intelligence, and predictive analytics to meet their business needs. As a former data scientist for the Cincinnati Reds, he performed in-depth research of advanced baseball physics measures using statistical techniques that include linear regression, linear classification, mixed models, GAM models, and machine learning methods such as XGBoost. Pete also has advanced knowledge of SQL, R, Python, and AWS.

Data Science
Machine Learning
Data Mining & Management
Business Intelligence
Predictive Analytics
Data Science Research
Data Analytics
SQL
Python
R
Amazon Web Services
Pete Melgren

Pete Melgren

Former data scientist for the Cincinnati Reds.

Data Science Developer

Pete is Available for Projects

Work with Pete

Employment Highlights

Data Science Consultant

Independent

January 2019 - Present (2 years 5 months)

Data Scientist

Cincinnati Reds

January 2016 - October 2018 (2 years 9 months)

Associate Economist

Moody’s Analytics

December 2013 - January 2016 (2 years 1 month)

Education Highlights

B.S.

University of Michigan Ann Arbor

September 2009 - May 2013 (3 years 8 months)

Portfolio

GitHub

GitHub

Resume

Data Science Consultant

Independent

January 2019 - Present (2 years 5 months)

  • Consulted with cross-industry clients on the use of data science concepts such as machine learning, data mining, business intelligence, and predictive analytics to meet their business needs. 
  • Wrote ETL scripts, mined and cleaned data, trained machine learning models, built visualizations and dashboards, and completed other data science tasks as needed to implement these solutions.
  • Performed specific tasks for clients within the field of data science or analytics.

Data Scientist

Cincinnati Reds

January 2016 - October 2018 (2 years 9 months)

  • Developed expertise of baseball statistics and used this expertise to help guide decision making across all baseball-facing aspects of the Reds’ front office.
  • Performed in-depth research of advanced baseball physics measures using statistical techniques that include linear regression, linear classification, mixed models, GAM models, and machine learning methods such as XGBoost.
  • Used SQL, Python, and R heavily to perform this analysis. Developed packages in R and created interactive online tools using Shiny.
  • Worked closely with baseball systems on a variety of ETL jobs using Python and SQL.

Associate Economist

Moody’s Analytics

December 2013 - January 2016 (2 years 1 month)

  • Supported the development of economic forecast products by training econometric models and writing programs to ensure data quality.
  • Established programming expertise and trained other analysts to write code in database software and statistical languages.
  • Analyzed economic data and delivered written insights to customers.

Education

B.S., Applied Mathematics & Economics

University of Michigan Ann Arbor

September 2009 - May 2013 (3 years 8 months)