Kolawole Q.

Kolawole Q. has an extensive work experience starting in 2015, where they served as the Manager, Maintenance & Predictive Analytics at The Goodyear Tire & Rubber Company. Kolawole then worked at Cisco as a Data Scientist - Data Quality Manager from December 2016 to June 2017. Following that, they joined John Deere as a Senior Software Engineer from January 2018 to January 2019. Kolawole then moved to Caterpillar Inc. as a Data Scientist III from February 2019 to November 2019. From March 2020 to December 2021, they worked at Honeywell as a Principal Data Engineer. Next, they worked at Caterpillar Inc. as a Sr Data Scientist from June 2021 to May 2022. Currently, they hold the position of Principal Information Architect at Context Labs BV, which they started in May 2022.

Kolawole Q. has a diverse education history. Kolawole obtained a Master's degree in Software Engineering from East Carolina University in 2018. Prior to that, they pursued a Master of Science (MSc) in Quality Assurance at California State University-Dominguez Hills from 2014 to 2017. In 2013, Kolawole undertook coursework in Electrical Engineering, specializing in Embedded System & VLSI Design and Antenna & Microwave Engineering, at Minnesota State University, Mankato. Kolawole completed their BSc in Electrical/Electronics Engineering at Moshood Abiola Polytechnic Abeokuta from 2009 to 2010. Kolawole also holds an Associate's degree in Electrical and Electronics Engineering from The Federal Polytechnic Ilaro, which they achieved in 2006.

In addition to their formal education, Kolawole has obtained various certifications. In August 2020, they earned the Certified Knowledge Engineering Specialist and Certified Semantic Integration Expert certifications from Semantic Web Company GmbH (SWC). Kolawole became a Certified Software Tester in December 2017 through ASTQB - Official Page - American Software Testing Qualifications Board. Furthermore, in March 2017, Kolawole completed a certification in Key Drivers Analysis and Optimization with Probabilistic Structural Equation Models with Bayesian Network & BayesiaLab from Bayesia USA.