Collectors is the leading creator of innovative technology that provides value-added services for collectors worldwide. We grade, authenticate, vault and sell millions of record-setting collectibles, all while modernizing and digitalizing the process to further our mission of helping collectors pursue their passions. We’re always on the lookout for talented people to join our growing team.

Our services span collectible coins, trading cards, Funko Pops!, video games, event tickets, autographs, and memorabilia. Our subsidiaries include PSA, PCGS, WATA, Card Ladder, Goldin, and the Long Beach Expo collectibles trade show.

Since our founding in 1986, we have graded and authenticated millions of items. We employ more than 1,700 people across our headquarters in Santa Ana and offices in Jersey City, Seattle, Hong Kong, Paris, Shanghai, and Tokyo.

We’re looking for a Data Annotation Specialist temp or intern to work full time (40 hours per week) on an 8 week remote contract assignment with our Shared Services Team. As a Data Annotation Specialist, your day to day will essentially focus on accurately labeling, tagging and categorizing large datasets of images uploaded into our internal software.

Our Shared Services Team is responsible for building modern cloud based applications, integrations (APIs and asynchronous) and scalable architectures that power software solutions across the organization. On the job training is provided.

What You’ll Do:

• Prepare and enter large volumes of data with precision and efficiency for various machine learning projects
• Collaborate with other team members to ensure data is labeled consistently and accurately
• Perform quality control checks to maintain high levels of data accuracy
• Communicate effectively with stakeholders to understand project requirements
• Continuously improve annotation / data entry processes to increase efficiency and reduce errors
• Identifying, reformatting and drawing boxes on datasets accordingly

Who You Are: 

• You are motivated about reaching goals and meeting deadlines
• You have a keen eye for accuracy with strong attention to detail
• You have the ability to maintain focus for extended periods of time
• You are passionate about doing repetitive tasks
• You are comfortable working in a high volume, fast paced environment
• You are able to work independently and as part of a team
• You are computer savvy and familiar with data entry skills and data management systems 
• Additional skills that would be useful:
• Proficient in using annotation tools and software
• Familiarity with data formats such as CSV, JSON, and XML
• Familiarity with or open to learn machine learning concepts, programming (Python) and querying database (SQL) is a plus

Training you will receive in the role:

• Annotation Tools: The candidate will receive training on annotation software to efficiently annotate large datasets. They will learn how to use these tools to mark-up and label data to support machine learning models.
• Data Management: The candidate will receive training on data management systems to ensure they can effectively organize and manage large datasets. They will learn about the importance of data quality and consistency, and how to maintain accurate and up-to-date data records.
• Quality Control: The candidate will receive training on quality control methods to ensure the annotated data is of high quality and accuracy. They will learn how to identify and resolve annotation errors and inconsistencies, and how to maintain consistent annotation practices across the team.
• Machine Learning Concepts: Candidates that are interested will receive training on the basics of machine learning concepts and techniques. They will learn how annotated data is used to train machine learning models, and how to assess the performance of these models.

Physical Requirements:

• Sitting and standing for extended periods of time.

Hourly Range: The hourly range for this position is $20-$25. Entry level positions generally start at an hourly rate of $17. Actual compensation in this range will be based on a variety of non-discriminatory factors, including location, job level, prior experience, and skill set.

Candidates must be authorized to work in the United States.

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