Case Study C, recommendations

Leslie Rose

Phone: 425-555-1212
Email: leslie.rose@gmail.com
LinkedIn: in/leslierose35

Education

Prestigious University

  • B.S. in Physics and Informatics expected in June 2024
  • Relevant and Planned Coursework
    • Beginning Scientific Computing
    • Intermediate Data Programming
    • Data Structures and Algorithms
    • Foundational Skills for Data Science

Fictitious University

  • GPA 3.967 / 4.00
  • Relevant Coursework
    • Differential Equations
    • Linear Algebra
    • Calculus III
    • Intro Programming for Engineering

Long Beach High School

  • GPA: 4.00 / 4.00

Honors

  • Jack J. Murray General Physics Prize (2021)
  • National Merit Finalist, National AP Scholar, National Hispanic Scholar
  • Jamison Research Fellow

Work Experience

Collins Self Defense School

  • Lead instructor teaching full classes of students aged 4-7
  • Learned teaching and leadership skills from other experienced leaders
  • Implemented lesson plans to foster both learning and fun for the students

Projects

Machine Learning Analysis of Hourly Wage by Gender

  • Analysis and visualization of City of Seattle based on department and gender
  • Used machine learning techniques to predict gender from first names, then analyzed through various statistical methods

Chess Opening Guessing Program

  • Web scraped https://www.365chess.com/eco.php for various chess openings
  • Program will guess a chess opening name from input moves

Machine Learning Analysis of 911 Calls

  • Analysis of daily 911 phone calls in Seattle since 2006
  • Used Web scraping to gather the top Google results and guess causes for busiest 911 call days
  • Predicted future levels of 911 calls through machine learning model
  • Notice how the project titles emphasize “Machine Learning” and “Program.” We want the recruiter to see immediately that these projects are all about programming.
  • We keep the two column approach along with the color scheme. We adjust the widths of the columns until both columns have approximately the same length.
  • We have shortened many items considerably, losing smaller details. Think of the resume as a “teaser” trailer - we can omit some details for the interviewer to ask about.