Alex Johnson
Data Annotation Specialist & AI Training Expert
Boston, Massachusetts | (617) 555-8910 | alexjohnson@email.com
Professional Summary
Detail-oriented computer science professional with proven expertise in data annotation and AI training.
Demonstrated ability to accurately label complex datasets for machine learning applications while
maintaining high quality standards. Combines solid technical foundation in computer science with
hands-on experience in annotation methodologies across various AI applications. Seeking opportunities
to leverage data annotation skills in advancing AI-powered technologies.
Data Annotation & AI Training Experience
InnovateTech AI, Remote – Data Annotation Specialist
January 2023-Present
- Annotate diverse datasets including images, text, and video for machine learning model training
- Maintain 98% accuracy rate in labeling data across multiple annotation projects
- Create comprehensive taxonomies and annotation guidelines for team members
- Perform quality control checks on annotated datasets to ensure consistency
- Collaborate with machine learning engineers to improve annotation frameworks
- Specialize in complex annotation tasks including semantic segmentation, bounding boxes, and
entity recognition
- Develop efficient workflows that increased annotation productivity by 25%
EdTech Solutions, Remote – Content Quality Analyst
August 2022-Present
- Review and validate training data for AI-assisted learning systems
- Train junior annotators on proper data labeling techniques and standards
- Create detailed rubrics for consistent data classification across teams
- Develop common error libraries to improve annotation accuracy
- Participate in regular calibration sessions to maintain consistency across annotation teams
- Provide technical feedback for annotation tool improvements
- Contribute to data pre-processing pipelines to enhance annotation efficiency
DataCore Systems, Boston, MA – Junior Data Annotator
September 2021-July 2022
- Performed text annotation for natural language processing applications
- Tagged and classified data according to project-specific guidelines
- Identified and reported data quality issues to improve dataset integrity
- Achieved consistent quality scores above 95% in team evaluations
- Collaborated with project managers to clarify annotation requirements
- Participated in iterative improvement of annotation guidelines
- Trained on specialized annotation tools for different data types
MIT AI Research Lab, Cambridge, MA – Research Assistant
May 2021-August 2021
- Assisted in creating specialized datasets for computer vision applications
- Annotated images for object detection and recognition models
- Validated machine learning outputs for accuracy and consistency
- Contributed to research on efficient annotation methods for large datasets
- Participated in weekly team meetings to discuss annotation challenges
- Documented common annotation issues to improve guidelines
- Co-authored technical report on annotation best practices
Education
Bachelor of Science (B.S.) in Computer Science
Northeastern University, Boston, MA, 2018-2022
Concentration: Machine Learning and Data Science
GPA: 3.8/4.0
Notable Coursework: Data Structures & Algorithms, Machine Learning, Database Management Systems,
Computer Vision, Natural Language Processing
Certificate in Advanced Data Science
University of California, Berkeley (Online Program), 2022-2023
Specialization: Data Annotation & Preprocessing
Technical Skills
- Annotation Tools: CVAT, LabelImg, Supervisely, Prodigy, Amazon SageMaker Ground Truth,
Scale AI platform
- Data Types: Image annotation, text classification, semantic segmentation, named entity
recognition, sentiment analysis
- Programming Languages: Python, SQL, HTML/CSS, JavaScript basics
- Development Tools: Git, Jupyter Notebooks, Visual Studio Code, Docker basics
- AI/ML Frameworks: Basic knowledge of TensorFlow, PyTorch, scikit-learn
- Databases: MySQL, MongoDB basics
- Productivity Tools: Advanced Excel, Google Suite, Jira, Confluence
- Languages: English (Native), Spanish (Intermediate)
Projects & Certifications
- Projects:
o "Optimizing Data Annotation Workflows for Computer Vision Applications" -
Northeastern Capstone Project, 2022
o "Comparative Analysis of Annotation Tools for NLP Tasks" - Personal Research Project,
2023
o "Building an Efficient Data Pipeline for Machine Learning Models" - HackBoston Winner,
2022
- Certifications:
o Professional Data Annotation Specialist, DataCamp, 2023
o Machine Learning Data Preparation, Coursera (Google), 2022
o Python for Data Science, edX (Harvard), 2021
o SQL Database Management, Microsoft, 2022
Awards & Achievements
- Recognized as Top Performer in Data Annotation Quality, InnovateTech AI, 2023
- Best Technical Solution Award, Northeastern Hackathon, 2022
- Scored in top 5% in National Data Science Competition, 2021
