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Катерина
Project data annotator
City of residence:
Hatne
Ready to work:
Remote
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Kateryna Kazmirchuk
Cloud Point Annotator / LiDAR Data Specialist
CONTACT Phone: [open contact info ](look above in the "contact info" section)
Email: [open contact info ](look above in the "contact info" section)
Address: Kyiv (Hatne), Ukraine
SUMMARY Detail-oriented Data Annotator with 4 years of experience specializing in 3D Point Cloud
and LiDAR data labeling. Proficient in 3D cuboid bounding, semantic segmentation, and
sensor fusion (LiDAR + Camera). Proven track record of delivering high-quality training
data for autonomous vehicle (AV) systems and robotics with an accuracy rate of 98%+.
SKILLS Data Types: 3D Point Clouds (LiDAR), RGB Images.
Annotation Tasks: 3D Bounding Boxes (Cuboids), Semantic Segmentation, Instance
Segmentation, Object Tracking.
Tool: Segments.ai.
Technical Knowledge: understanding of spatial coordinates (X, Y, Z), point density,
and object classification (Vehicles, Pedestrians, Infrastructure).
Soft Skills: high attention to detail, ability to meet tight deadlines, analytical thinking,
and team collaboration.
EXPERIENCE Cloud Point Annotator | Outsight | Paris, France
March, 2022 – Present
Annotate complex 3D point cloud sequences for different projects using Segments tool.
Perform 3D cuboid labeling for dynamic objects (cars, cyclists, pedestrians) and static
environments.
Collaborate with QA teams to refine labeling guidelines and improve data quality by 15%.
Consistently meet or exceed daily KPIs, processing 200-300 frames/objects per shift.
EDUCATION National Technical University of Ukraine “Kyiv Polytechnic Institute” 2008-2014
Master II in Applied Physics, graduated cum laude
Professional in Physics, Mathematics and Technical Sciences
LANGUAGES English: Upper-Intermediate (B2)
Ukrainian: Native
Cloud Point Annotator / LiDAR Data Specialist
CONTACT Phone: [
Email: [
Address: Kyiv (Hatne), Ukraine
SUMMARY Detail-oriented Data Annotator with 4 years of experience specializing in 3D Point Cloud
and LiDAR data labeling. Proficient in 3D cuboid bounding, semantic segmentation, and
sensor fusion (LiDAR + Camera). Proven track record of delivering high-quality training
data for autonomous vehicle (AV) systems and robotics with an accuracy rate of 98%+.
SKILLS Data Types: 3D Point Clouds (LiDAR), RGB Images.
Annotation Tasks: 3D Bounding Boxes (Cuboids), Semantic Segmentation, Instance
Segmentation, Object Tracking.
Tool: Segments.ai.
Technical Knowledge: understanding of spatial coordinates (X, Y, Z), point density,
and object classification (Vehicles, Pedestrians, Infrastructure).
Soft Skills: high attention to detail, ability to meet tight deadlines, analytical thinking,
and team collaboration.
EXPERIENCE Cloud Point Annotator | Outsight | Paris, France
March, 2022 – Present
Annotate complex 3D point cloud sequences for different projects using Segments tool.
Perform 3D cuboid labeling for dynamic objects (cars, cyclists, pedestrians) and static
environments.
Collaborate with QA teams to refine labeling guidelines and improve data quality by 15%.
Consistently meet or exceed daily KPIs, processing 200-300 frames/objects per shift.
EDUCATION National Technical University of Ukraine “Kyiv Polytechnic Institute” 2008-2014
Master II in Applied Physics, graduated cum laude
Professional in Physics, Mathematics and Technical Sciences
LANGUAGES English: Upper-Intermediate (B2)
Ukrainian: Native
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The candidate's resume is posted at https://www.work.ua/resumes/16648063/