Resume

Cody Maughan

650 South Main Street #4303 Bountiful, Utah 84010
Phone: (443) 416-0306 E-Mail: [email protected]

Employment History

Data Scientist, Progressive Leasing December 2018 – Present

  • Created next company’s next generation of profit forecasting using deep learning models. Designed, trained, and validated neural network and xgboost models to help profile customer behavior and predict future customer lifetime value.

Data Analyst, Progressive Leasing April 2018 – December 2018

  • Analyzed company portfolio risk and provided reports to team members and company executives. Analyzed experiments and found explanations for unexpected experiment results. Worked on next generation of profit prediction engine and real time fraud detection technology.

Graduate Researcher, University of Utah June 2016 – February 2018

  • Conducted research on various data analysis research projects involving cancer genomics with big data sets. Wrote and tested code as well as provided new analysis techniques and improved algorithms for genomic data analysis. Interpreted, visualized, and presented results at international conferences.

Education

Bachelor of Science in Biological Engineering, Utah State University

  • Completed: May 2016 (Undergraduate GPA: 3.99 – Magna Cum Laude and Valedictorian of the College of Engineering)

Master of Science in Bioengineering, University of Utah

  • Completed: December 2018 (Graduate GPA: 4.00 – Recipient of Campbell Endowed Fellowship)

Education

  • Highly proficient in a variety of programming languages including Python, R, Java, and C#, as well as query languages, such as SQL and Cypher
  • Very experienced with deep learning techniques and using deep learning packages in python, such as keras and tensorflow
  • Extensive experience with data analysis and discovery techniques, including matrix decomposition techniques, machine learning, optimization techniques, statistical methods, etc.
  • Exceptional problem-solving skills, including the ability to structure problems in abstract mathematical frameworks and solve them with well-known techniques
  • Highly motivated independent learner and self-taught in many subjects including such areas as theoretical physics, game theory, functional calculus, and music theory