https://www.linkedin.com/in/omar-pinzon-bb***b**b/

OMAR PINZON

Tallahassee, Florida adym3u@r.postjobfree.com +1-850-***-**** EDUCATION

Florida State University August 2018 - May 2023

Bachelor of Science, Industrial Engineering

Cumulative GPA: 3.0/4.0

Relevant Coursework: Production Systems, Simulation of IE Systems, Materials & Processes, Engineering Economy, Operations Research, Management, Quality Control, Lean Applications. Saint Mary’s (Panama City, Panama) August 2014 – May 2018 Bachelor of Science (Honors Class)

CERTIFICATIONS AND SKILLS

Certifications: Six Sigma Green Belt (January 2023) Technical Skills: Data Analysis, Microsoft Word, Microsoft Excel, Minitab, Programming (C++, MATLAB, Python), Arena Simulation, Abaqus.

Languages: Spanish (Native), English (Fluent)

EXPERIENCE

PINZON-ULLOA S.A September 2018 – March 2020

Administration Assistant

Provided support to lawyers and other professionals in the office, such as drafting documents, organizing case files, and recommending new technology and systems to improve workflow and increase efficiency.

Tools Used: Templafy, DocuWare, and Microsoft Excel. RELEVANT PROJECTS

Tallahassee’s Waste Management Department August 2022 – May 2023

• Proposed a new scheduling system that balances the residential pickup routes to optimize labor utilization and on-time pickup.

Ergonomic Analysis for Danfoss August 2022 – December 2023

• Examined the ergonomic problems that workers faced in their daily job (lifting, carrying, and assembling parts). We proposed a solution which involved formulating an economic analysis to purchase a product with the goal of preventing or minimizing the worker’ risk of injury. Face Shields (PPE) Production January 2022 – May 2022

• Developed a plan with a team to build a specialized facility of face shields in the Tallahassee region. We were also required to design the face shields taking into consideration the best suitable material.

Process Improvement Study August 2022 – December 2022

• Conducted multifactor experiments to analyze the impact of several aspects on the flight distance of paper airplanes. To do so, we established predictive models for the mean flight distance as a function of the controllable factors.