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Olena
Data Annotator
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ML Data Associate |Data Annotator| Data Labeler| Data
Quality Control
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Summary
I have 7 years of experience in image and video annotation, dataset quality control, and team coordination for
AI and computer vision projects. Energetic, responsible, and positive professional, focused on delivering
results. Skilled in managing annotation processes, training teams, and ensuring data accuracy, with hands-on
experience in CVAT, Snezhana, and Label Studio, as well as cross-functional collaboration with data engineers
and QA teams. Committed to professional growth and ready to make a meaningful contribution to
organizational goals.
Experience
ML Data Associate, SQUAD 04/2025 – 11/2025
Perform object annotation on images and prepare materials for
• Kyiv
annotation.
Process and edit videos to prepare them for annotation.
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Remove unnecessary fragments.
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Check the quality of completed work.
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Audit annotations and correct errors.
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Team Leader, SQUAD 01/2021 – 01/2025
Managing team who provide recheck and labelling process;
• Kyiv
daily controlling team's results and providing individual feedback;
•
quick switching team on priority tasks;
•
providing team performance reports to management,
•
performance review;
resolving issues, motivating team and maintaining team's spirit;
•
providing team meetings to discuss tasks, corner cases and etc.;
•
writing and creating Niagara and Snezana documentation in
•
Confluence/Jira.
Senior Quality Operator, SQUAD 02/2020 – 01/2021
Managing team who provide recheck and quality process. Kyiv
Data Quality Operator, Ring Ukraine 11/2019 – 02/2020
conduct video verification process;
• Kyiv
register and report markup mistakes;
•
pre-validate pilot task quality requirements;
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identify data anomalies and outliers.
•
Data Entry Operator, Ring Ukraine 12/2017 – 10/2019
Annotation of various types of data (images, videos, audio);
• Kyiv
working with different annotation tools;
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recognition and removal of objects with high precision;
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clear execution of instructions;
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attention to detail; adherence to deadlines.
•
training neural networks of smart doorbells and surveillance
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cameras by annotating photo and video materials.
testing and processing neural networks algorithms;
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working with Label Studio, CVAT, MySQL, Docker, Jira,
•
Confluence.
collecting data from smart devices for further neural networks
•
processings.
Education
Master's degree, Business activity management, 2007 – 2013
Simon Kuznets Kharkiv National University of Economics Kharkiv
Skills
Fast learning ability Detail-oriented and results- focused
Communicate effectively with team members Jira, Confluence, MS Office
Segment different objects and details in images
Languages
English Ukrainian
Hobbies and interests
Fitness and Well-being Books and music Travel and cultural exploration
Art Photography
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