ZipRecruiter

Log In

1

Data Annotation Services Jobs in New York (NOW HIRING)

Aquent

Senior AI Data Operations Analyst

Manhattan, NY · On-site +1

$47 - $51/hr

We are seeking a Senior AI Data Operations Analyst to join our media clients Services ... Execute & Champion Data Annotation: Perform hands-on data annotations and lead larger, cross ...

Meta

Sourcing Manager, Data Operations

New York, NY · Remote

$139K/yr

... service levels) * A deep understanding of balancing speed, quality, and cost in sourcing decisions ... 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

... AI data annotation and collection vendors • Proactively identify, track, and manage risks and ... service levels) • A deep understanding of balancing speed, quality, and cost in sourcing ...

Smarsh

Lead Data Scientist

New York, NY

... servicing/managing day to day data requests and analysis. This role also offers a unique ... Data annotation and quality review * Exploratory data analysis and model fail state analysis

Smarsh

Lead Data Scientist

New York, NY · On-site +1

... servicing/managing day to day data requests and analysis. This role also offers a unique ... Data annotation and quality review * Exploratory data analysis and model fail state analysis

Project Healthy Minds

Services Data Lead

New York, NY · Remote

$75 - $100/hr

Real experience running data operations with a human-in-the-loop or annotation component ... Experience building or maintaining a services dataset or provider directory The hourly rate for ...

Project Healthy Minds

Services Data Lead

New York, NY · On-site

$75 - $100/hr

... annotation component , including directing distributed specialists to a quality bar. • You've ... data interoperability standards. • Experience building or maintaining a services dataset or ...

next page

Showing results 1-20

All JobsData Annotation Services JobsData Annotation Services Jobs in New York

Data Annotation Services information

How hard is it to get hired by data annotation?

Getting hired for data annotation services typically requires basic computer skills, attention to detail, and the ability to follow instructions. Many positions are entry-level and may not require prior experience, but familiarity with annotation tools and good accuracy can improve chances of employment.

What are the key skills and qualifications needed to thrive in Data Annotation Services, and why are they important?

To excel in Data Annotation Services, strong attention to detail, data literacy, and a foundational understanding of data labeling processes are essential, often requiring a high school diploma or equivalent. Familiarity with annotation platforms, labeling tools, and sometimes basic knowledge of scripting or data management systems is typically expected. Strong work ethic, consistency, and effective communication skills help individuals stand out in collaborative, deadline-driven environments. These capabilities ensure high-quality, accurate labeled data, which is critical for training reliable machine learning models.

Does data annotation actually pay you?

Data annotation services typically pay workers for labeling data used in machine learning models. Payment rates vary depending on the platform, task complexity, and experience, with many jobs offering hourly or per-task compensation. Reliable platforms often require basic skills in data handling and attention to detail.

Is data annotation real or fake?

Data annotation is a legitimate job that involves labeling data such as images, text, or videos to train machine learning models. It requires attention to detail and familiarity with annotation tools, and it is widely used in AI development. The work is real and essential for creating accurate AI systems.

What is the difference between Data Annotation Services vs Data Labeling Specialists?

AspectData Annotation ServicesData Labeling Specialists
CredentialsTypically no formal credentials required; focus on trainingOften have training in specific tools or industry standards
Work EnvironmentCollaborative, often remote or in-office teamsSimilar, working in teams or independently on labeling tasks
Industry UsageUsed by AI/ML companies for training datasetsEmployed in similar settings, focusing on labeling data for AI models
Search & Comparison IntentUnderstanding services offered for data preparationLooking for roles or tasks related to data labeling

Data Annotation Services encompass the broader process of preparing and annotating data for AI and machine learning projects, often provided by specialized companies. Data Labeling Specialists are individual professionals or team members who perform the actual labeling tasks within these services. While both are closely related, services refer to the overall offering, whereas specialists are the personnel executing the work.

What are some common challenges faced when working in data annotation services, and how can I address them?

In data annotation services, one common challenge is maintaining consistency and accuracy, especially when handling large datasets or ambiguous data points. Clear annotation guidelines and regular communication with team leads help ensure that everyone interprets the data similarly. Additionally, repetitive tasks can lead to fatigue, so it's important to take scheduled breaks and leverage available annotation tools to streamline workflows. Collaborating with peers to discuss edge cases also helps improve overall data quality and fosters a supportive team environment.

What does a data annotation job do?

A data annotation job involves labeling or tagging data such as images, text, or videos to help train machine learning models. Workers use tools to add metadata, which improves the accuracy of AI systems, often working remotely with flexible schedules and requiring attention to detail. Knowledge of annotation tools and data quality standards is beneficial.

What are data annotation services?

Data annotation services involve labeling or tagging data—such as images, text, audio, or video—to make it understandable for machine learning models. These services are essential in training artificial intelligence systems to recognize patterns, objects, or other relevant information in raw data. Companies use data annotation to improve the accuracy and effectiveness of AI applications, such as self-driving cars, chatbots, and image recognition. Professional annotators or specialized platforms often perform these tasks to ensure high-quality, consistent results.
What are popular job titles related to Data Annotation Services jobs in New York? For Data Annotation Services jobs in New York, the most frequently searched job titles are:
What job categories do people searching Data Annotation Services jobs in New York look for? The top searched job categories for Data Annotation Services jobs in New York are:
What cities in New York are hiring for Data Annotation Services jobs? Cities in New York with the most Data Annotation Services job openings:
Data Annotation Services jobs near you
Infographic showing various Data Annotation Services job openings in New York as of July 2026, with employment types broken down into 2% Locum Tenens, 34% Full Time, 26% Part Time, 1% Contract, 36% Nights, and 1% Summer. Highlights an 56% Physical, 1% Hybrid, and 43% Remote job distribution.

Senior AI Data Operations Analyst

Aquent

Manhattan, NY • On-site, Remote

$47 - $51/hr

Temporary

Medical, Retirement

Posted 7 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.
#LI-CF1

Apply