Milena K.
About Milena K.
Milena K. is a Data Imagery Technician at Semios in Vancouver, British Columbia, where she has worked since 2020. She holds a Bachelor of Arts in Economics from the Vancouver School of Economics at UBC, where she studied from 2018 to 2023.
Work at Semios
Milena K. has been employed at Semios as a Data Imagery Technician since 2020. In this role, she is based in Vancouver, British Columbia, Canada. Her responsibilities include annotating images to identify specific crop stages and pests, which aids in the development of agricultural models. Additionally, she evaluates the accuracy of weather, disease, crop, and pest models that are significant to agriculture. Milena also performs quality control for both internal and customer-facing components of Semios' platform, ensuring the reliability and effectiveness of the data provided.
Education and Expertise
Milena K. studied at the Vancouver School of Economics at the University of British Columbia (UBC), where she earned a Bachelor of Arts in Economics from 2018 to 2023. Her academic background provides her with a solid foundation in economic principles, which she applies in her current role at Semios. Prior to her university education, she attended Semiahmoo Secondary from 2017 to 2018, which contributed to her early academic development.
Background
Before joining Semios, Milena K. worked as a Crew Member at The Homegrown Group for three months in 2019 in Kirkland, Washington, United States. This experience provided her with foundational skills in teamwork and customer service, which are beneficial in her current role. Her transition from a crew member to a data imagery technician reflects her growth and development in the field of data analysis and agricultural technology.
Technical Skills
In her position at Semios, Milena K. utilizes a variety of tools to perform her duties effectively. She is proficient in Microsoft Office and Google Suite, as well as internal user-interfaces specific to Semios. These technical skills enable her to manage data efficiently and contribute to the quality control processes within the company.