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James Donovan

James Donovan

Systems Engineer

Manufacturing / Mechanical

San Francisco, San Francisco County

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About James Donovan:

Innovative and analytical engineer with graduate education in Data Science and Chemical Engineering. Experience executing diverse projects in Data Analytics and Systems Engineering while exhibiting strong organization skills and a solid work ethic.

Experience

Systems Engineer & Data Analyst - Johnson & Johnson; San Francisco, CA. May 2022 - Present

●  Creating metrics & visualizations to guide improvements to the Monarch robotic endoscopy platform.

●  Translating feature owner data requirements into scripts and reports based on a Pyspark, Hive, and AWS S3 stack.

●  Overseeing and delivering platform-wide data analysis systems for the ureteroscopic robot configuration.

Systems Engineer – Rovisys; Raleigh, NC Sep. 2020 - May 2022

●  Provided turnkey systems integration services including PLC/HMI code, SCADA network design, onsite commissioning, and legacy systems migration.

●  Integrated ML models and closed-loop control with Quartic AI to enhance manufacturing operations.

●  Learned to quickly identify and adapt to customer needs when working with new systems and technologies.

Research Assistant – NCSU Chemical Engineering Dept; Raleigh, NC. Aug. 2019 - May 2020

● Programmed Python-based process control logic, GUIs, and data visualization for experimental thin film reactors created by the Parsons Research Group.

Education

Bachelor of Science in Chemical Engineering, North Carolina State University with Minor in Computer Programming; Magna Cum Laude.

Graduate Coursework: Process Simulation, Green Chemical Engineering, Biochemical Engineering, and Statistical Mechanics.

Leadership: NCSU Student Government: Sustainability Department Director. PIKE - Alpha Epsilon: Founding Father & Internal VP.

Micro Masters in Statistics and Data Science, Massachusetts Institute of Technology Coursework: Probability, Statistics, Machine Learning, and Data Analysis. All courses and the capstone exam featured statistical analysis with Python (Pandas, PyTorch, etc.)

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