Leo J. Robinovitch

Selected Employment

• Using Scala, Typescript, Python, MongoDB, Kubernetes, Docker, and Shell to build enterprise Data Science tooling.

• Lead Python-based statistical analysis on the Model 3 drive inverter, resulting in a 3x improvement in semiconductor reliability
• Drove a 20% improvement in weekly yield by creating and automating detailed visibility reports into problem areas on the drive inverter manufacturing line using Python, Matplotlib, Bokeh, and Apache Airflow
• Created and maintained an application suite for reliability, manufacturing, and design tooling used by Power Electronics, Reliability, Manufacturing and Firmware teams with Python, Flask, HTML/CSS, MySQL, MongoDB, Docker, and Ansible
• Created and maintained Python packages for Weibull reliability analysis, state space thermal modeling, and quantification of wear accumulation for specific vehicle failure modes

• Implemented reliability-driven driver data transform model in Python, simulating driver behavior in unreleased vehicles using behavior in existing vehicles
• Created final exploded views for the Model 3 drivetrain using CATIA

• Designed and manufactured testing apparatus and prototyping hardware, including Arduino-controlled force applicator, 3D printer, and standards of quality control applied to 4k+ products/yr

Education

• Dean’s Honor List every year; co-created and lead a Data Science club 2016 - 2017

• 12-week self driven programming retreat focusing on foundations of Computer Science, Statistics, Probability and Software Engineering
• Documented at theleo.zone

Skills and Interests

• colorcontroversy.com, covid19medstudents.ca
• Built web scraper in Python that emailed me when apartments within my price range and location preferences were posted
• Created my own mini version of Mint in Python to assist in my financial planning and budgeting