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Data Annotation Research Jobs in New York (NOW HIRING)

Aquent

Senior AI Data Operations Analyst

Manhattan, NY · On-site +1

$47 - $51/hr

Present qualitative findings, data trends, and quality risks clearly to product, design, research, and engineering leads. Who You Are * Data Quality / Annotation Background: Proven experience in data ...

Welocalize, Inc.

Data Quality Analyst

New York, NY · On-site

The ideal candidate will have a foundational understanding of machine learning, data annotation ... User Experience Research team. * Implement basic quality control measures and ensure the ...

Welocalize, Inc.

Data Labeling Associate

New York, NY

$17.50 - $22.75/hr

The ideal candidate will have a foundational understanding of machine learning, data annotation ... User Experience Research team. * Implement basic quality control measures and ensure the ...

Meta

Sourcing Manager, Data Operations

New York, NY · Remote

$139K/yr

As Sourcing Manager, Data Operations, you'll work closely with business and research teams across ... Experience in managing high-volume data annotation sourcing programs * Demonstrated ability to ...

Meta

Sourcing Manager, Data Operations

New York, NY · On-site

$139K - $196K/yr

As Sourcing Manager, Data Operations, you'll work closely with business and research teams across ... annotation and collection vendors • Proactively identify, track, and manage risks and issues ...

Mecka AI

Human Data Architect, Quality

New York, NY · On-site

$130K - $160K/yr

... annotation org executed against in production. * Worked directly with research scientists at ... You believe data quality is a design problem, not a process problem. * Precise about definitions ...

Smarsh

Lead Data Scientist

New York, NY · On-site +1

... based research and generate insights from large data sets with a hands-on/can do attitude of ... Data annotation and quality review * Exploratory data analysis and model fail state analysis

Smarsh

Lead Data Scientist

New York, NY

... based research and generate insights from large data sets with a hands-on/can do attitude of ... Data annotation and quality review * Exploratory data analysis and model fail state analysis

Neon Mobile, Inc

Data Ops Lead

New York, NY · On-site +1

$150K - $190K/yr

Standing up human transcription, annotation and other operations, largely overseas, that make it ... and research teams at frontier labs to translate their exact specifications into deliverable ...

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All JobsData Annotation Research JobsData Annotation Research Jobs in New York

Data Annotation Research information

What qualifications do I need for data annotation?

Data annotation research roles typically require basic computer skills, attention to detail, and familiarity with annotation tools or platforms. A high school diploma or equivalent is usually sufficient, though some positions may prefer experience with data labeling, machine learning concepts, or specific software. Strong communication skills and the ability to work independently are also beneficial.

What are some common challenges faced in Data Annotation Research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

Does data annotation actually pay?

Data annotation research jobs typically pay hourly or per task rates, with wages ranging from minimum wage to higher rates depending on experience and complexity of the work. Many positions are freelance or remote, requiring basic skills in data labeling tools and attention to detail. Payment is generally reliable, but rates vary by employer and project.

How hard is it to get hired by data annotation?

Getting hired for a data annotation research role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible for those with the right skills and reliability.

What is the difference between Data Annotation Research vs Data Labeling Specialist?

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs require attention to detail and often use tools like labeling platforms or software, making them a legitimate employment opportunity in the tech industry.

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

What are the key skills and qualifications needed to thrive as a Data Annotation Researcher, and why are they important?

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.
What are popular job titles related to Data Annotation Research jobs in New York? For Data Annotation Research jobs in New York, the most frequently searched job titles are:
What job categories do people searching Data Annotation Research jobs in New York look for? The top searched job categories for Data Annotation Research jobs in New York are:
What cities in New York are hiring for Data Annotation Research jobs? Cities in New York with the most Data Annotation Research job openings:
Data Annotation Research jobs near you

Senior AI Data Operations Analyst

Aquent

Manhattan, NY • On-site, Remote

$47 - $51/hr

Temporary

Medical, Retirement

Posted 6 days ago

Job description

Placement Type:
Temporary
Salary:
$47-51 Hourly
W2, Benefits and 401k matching
Start Date:
Aug 10, 2026
NOTE: This is a remote role but must work EST hours. This is for a MAT leave.
We are seeking a Senior AI Data Operations Analyst to join our media clients Services Recommendations team. This team owns the Home page experience-what millions of listeners see and interact with every day across music, podcasts, audiobooks, and more.
In this role, you will sit within the core product organization to ensure our recommendation engines and AI/LLM-powered features deliver high-quality, relevant experiences. You will act as a key driver of data quality and data annotation strategy, bridging the gap between product managers, data scientists, and engineers to build the datasets needed to train and evaluate our next-generation agentic features.
This is a hands-on, highly collaborative role focusing on qualitative data analysis, evaluation frameworks, and human-in-the-loop AI quality.
What You'll Do
  • Execute & Champion Data Annotation: Perform hands-on data annotations and lead larger, cross-functional annotation sessions to generate high-quality training datasets for recommendation models.
  • Define Quality Standards: Establish criteria, metrics, and qualitative success measures for core Home page features and the LLM judges evaluating them.
  • Run Structured Qualitative Evaluations: Design and execute qualitative testing using internal tools, keeping human judgment at the center while utilizing AI/LLM tools to scale evaluation efforts.
  • Support Flagship AI Initiatives: Partner on major, publicly announced product initiatives (e.g., taste profile and agentic home experiences).
  • Build Reusable Frameworks: Improve and maintain evaluation processes, guidelines, and documentation adopted across product groups.
  • Communicate Insights: Present qualitative findings, data trends, and quality risks clearly to product, design, research, and engineering leads.
Who You Are
  • Data Quality / Annotation Background: Proven experience in data annotation, data quality, or product/content quality analysis with direct ownership over evaluation workflows.
  • Strong Qualitative & Analytical Skills: Highly comfortable running structured qualitative evaluations, handling large data sets, and turning subjective feedback into clear quality metrics.
  • AI/ML Familiarity: Strong functional understanding of machine learning product development and how ML/LLM/agentic features are evaluated and trained. (Note: You do not need to write code or build models, but you must understand how data quality impacts AI outputs).
  • Process & Framework Builder: Demonstrated ability to create or refine evaluation frameworks and guidelines that help team members maintain quality standards.
  • Strong Communicator: Excellent written and verbal communication skills, comfortable presenting findings and guiding cross-functional teams through evaluation initiatives.
  • Tool Proficiency: Comfortable working with standard data tools (Excel, Google Sheets) and learning internal proprietary annotation/eval platform tools.
Nice-to-Haves:
  • Experience in media, music, or streaming entertainment platforms (though data annotation experience in other tech industries is fully welcome).

The target hiring compensation range for this role is $47.00/hr to $51.00. Compensation is based on several factors including, but not limited to education, relevant work experience, relevant certifications, and location.
**About Skill:**
Skill connects the best professional, IT, engineering, financial and administrative talent with the world's biggest brands. Our eligible talent get access to benefits such as health benefit contributions, retirement plans with match and flexible spending accounts.
Skill is an equal-opportunity employer. We evaluate qualified applicants without regard to age, race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, and other legally protected characteristics. We're about creating an inclusive environment-one where different backgrounds, experiences, and perspectives are valued, and everyone can contribute, grow their careers, and thrive.
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