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Day Data Annotation Jobs in Redmond, WA (NOW HIRING)

WHAT YOU'LL DO * Execute Data labelling and annotation tasks across speech and voice datasets ... Paid Vacation (6 days) * Paid Company Holidays * Paid Sick Leave * Employee Assistance Program

WHAT YOU'LL DO * Execute Data labelling and annotation tasks across speech and voice datasets ... Paid Vacation (6 days) * Paid Company Holidays * Paid Sick Leave * Employee Assistance Program

WHAT YOU'LL DO * Execute Data labelling and annotation tasks across speech and voice datasets ... Paid Vacation (6 days) * Paid Company Holidays * Paid Sick Leave * Employee Assistance Program

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Day Data Annotation information

What are the key skills and qualifications needed to thrive as a day data annotation specialist?

To excel as a Day Data Annotation Specialist, you need strong attention to detail, data entry accuracy, and a solid understanding of the subject matter being annotated, often supported by a high school diploma or relevant experience. Familiarity with annotation tools, spreadsheets, and data management software is typically required. Excellent concentration, time management, and clear communication skills help professionals stand out in this role. These abilities are crucial to ensure high-quality, consistent data labeling that directly impacts the performance of machine learning models and downstream business applications.

What is a day data annotation job?

Day Data Annotation jobs involve reviewing and tagging data, such as images, text, audio, or video, during regular daytime hours. Annotators help prepare datasets for machine learning and artificial intelligence by labeling or categorizing information according to specific guidelines. This work is essential for training algorithms to recognize patterns, objects, or language. Day Data Annotation can be done remotely or in-office, and it often requires attention to detail and good communication skills.

What is the difference between Day Data Annotation vs Data Labeler?

AspectDay Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, collaborative teamsRemote or on-site, independent work
Industry UsageAI/ML companies, tech firmsAI/ML, data processing companies
Job FocusAnnotating data for machine learning modelsLabeling data to train AI systems

Day Data Annotation and Data Labeler roles are similar, focusing on preparing data for AI. Day Data Annotation often involves more detailed annotation tasks, while Data Labelers may perform broader labeling activities. Both roles require basic technical skills and are vital in AI development across tech industries.

What are some common challenges faced by day data annotation specialists and how can they be addressed?

Day Data Annotation specialists often encounter challenges such as maintaining high accuracy while handling repetitive tasks, interpreting ambiguous data, and meeting tight deadlines. To address these, it's important to develop strong attention to detail, use project guidelines as references, and communicate with team leads or peers when uncertainties arise. Many organizations also provide regular feedback and quality assurance checks, which help annotators improve their performance and consistency over time.

Data Annotation Specialist - Seattle (On Site)

Welocalize

Seattle, WA • On-site

Full-time

Re-posted 20 days ago


Welocalize rating

6.5

Company rating: 6.5 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

327th of 481 rated business services


Job description

Job Summary:
Welo Global is a company focused on advancing AI technologies, and they are seeking a Data Analyst to join their team. This role involves testing new AI products, conducting data annotation, and collaborating on machine learning model updates to ensure high-quality data for AI solutions.
Responsibilities:
• Test new AI products and provide actionable feedback to improve functionality and user experience.
• Conduct detailed data annotation and quality assurance of natural language datasets following established guidelines.
• Collaborate in updating and refining machine learning models to boost accuracy and effectiveness.
• Analyze data for consistency, relevancy, and alignment with project goals.
• Perform quality control to identify and report anomalies, error patterns, and discrepancies.
• Use basic data analysis methods to extract insights and support continuous improvement.
• Prepare clear and concise reports on findings, including observations on data quality, AI model performance, and user feedback.
Qualifications:
Required:
• Must have valid work authorization in the US (Welocalize does not sponsor VISAs at this time).
• To verify work authorization as is required by Federal law (I-9 process), all new employees must complete a live video verification with their selected IDs and provide photos of these selected IDs within their first 3 days of employment.
• In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete the required employment eligibility verification form upon hire.
Preferred:
• University degree in linguistics, translation, or a related field.
• 3-5 years of professional linguistics experience.
• Strong analytical skills with the ability to detect patterns and anomalies.
• Excellent communication skills and the ability to work collaboratively in a fast-paced environment.
• Adaptability to evolving priorities and project requirements.
Company:
Welocalize provides translation supply chain management solutions that deliver market-ready, translated content. Founded in 1997, the company is headquartered in Frederick, USA, with a team of 1001-5000 employees. The company is currently Late Stage.

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