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Shena Sudell

AI Data Annotator

USA flag
Houston, Usa
ExpertAppenInternal Proprietary ToolingTelus

Key Skills

Software

AppenAppen
Internal/Proprietary Tooling
TelusTelus

Top Subject Matter

AI model training and evaluation

Top Data Types

ImageImage
VideoVideo
TextText
AudioAudio

Top Task Types

Classification
Object Detection
Text Generation
Computer Programming Coding
Evaluation Rating
Transcription
Prompt Response Writing SFT
Fine Tuning
Segmentation

Freelancer Overview

AI Data Annotator. Core strengths include N and A. Education includes Bachelor of Science, The University of Texas at Austin (2008) and Master of Science, The University of Texas at Austin (2012). AI-training focus includes data types such as Image, Video, and Text and labeling workflows including Classification.

ExpertFrenchGermanEnglishSpanish

Labeling Experience

AI Data Annotator

ImageClassification
Served as an AI Data Annotator at Turing, performing a variety of data labeling and annotation tasks for machine learning and AI model training. Managed high-volume annotation projects involving images, audio, video, and text datasets to support diverse AI applications. Ensured data quality and consistency through careful application of guidelines and comprehensive evaluation techniques. • Conducted pairwise comparisons and content evaluation for AI models. • Tagged and classified objects and segments across multimedia datasets. • Performed counting, categorization, and object identification tasks with high accuracy. • Reported inconsistencies and contributed to the improvement of dataset reliability.

Served as an AI Data Annotator at Turing, performing a variety of data labeling and annotation tasks for machine learning and AI model training. Managed high-volume annotation projects involving images, audio, video, and text datasets to support diverse AI applications. Ensured data quality and consistency through careful application of guidelines and comprehensive evaluation techniques. • Conducted pairwise comparisons and content evaluation for AI models. • Tagged and classified objects and segments across multimedia datasets. • Performed counting, categorization, and object identification tasks with high accuracy. • Reported inconsistencies and contributed to the improvement of dataset reliability.

2022 - 2024

Education

T

The University of Texas at Austin

Doctor of Philosophy, Mathematics

Doctor of Philosophy
2015 - 2020
T

The University of Texas at Austin

Master of Science, Mathematics and Statistics

Master of Science
2010 - 2012

Work History

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