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Data Labelling Jobs in Washington, DC (NOW HIRING)

Data Scientist

Ashburn, VA · On-site

$99K - $164K/yr

We are seeking a Data Scientist to join our team and support our client in Ashburn, VA. The ideal ... Extract, clean, transform, label, annotate, and interpret image, biometric, transactional, and ...

Data Scientist

Ashburn, VA · On-site

$99K - $164K/yr

We are seeking a Data Scientist to join our team and support our client in Ashburn, VA. The ideal ... Extract, clean, transform, label, annotate, and interpret image, biometric, transactional, and ...

Transferring label task information via API-based movement between platforms * Build software tools to: * Filter and visualize data geospatially * Allow feedback entry and data analysis * Integrate ...

We are seeking a Data Scientist to join our team and support our client in Ashburn, VA. The ideal ... Extract, clean, transform, label, annotate, and interpret image, biometric, transactional, and ...

Transferring label task information via API-based movement between platforms * Build software tools to: * Filter and visualize data geospatially * Allow feedback entry and data analysis * Integrate ...

Transferring label task information via API-based movement between platforms * Build software tools to: * Filter and visualize data geospatially * Allow feedback entry and data analysis * Integrate ...

Data Analyst

Washington, DC · On-site

$100 - $117/hr

Identify errors/omissions of variable formats or labels. * Document problems and proposed corrections before finalizing the data set. * Review the data files to document problems and proposed ...

Data Analyst

Washington, DC · Hybrid

$100K - $117K/yr

Identify errors/omissions of variable formats or labels. * Document problems and proposed corrections before finalizing the data set. * Review the data files to document problems and proposed ...

Data Analyst

Washington, DC · On-site

$100K - $117K/yr

Identify errors/omissions of variable formats or labels. * Document problems and proposed corrections before finalizing the data set. * Review the data files to document problems and proposed ...

Showing results 41-60

Data Labelling information

See Washington, DC salary details

$52.1K

$186.9K

$275.8K

How much do data labelling jobs pay per year?

As of Sep 5, 2026, the average yearly pay for data labelling in Washington, DC is $186,899.00, according to ZipRecruiter salary data. Most workers in this role earn between $151,200.00 and $192,500.00 per year, depending on experience, location, and employer.

What is a data labelling?

A Data Labelling job involves annotating data, such as text, images, audio, or video, to help train machine learning models. Labelers categorize or tag data by following specific guidelines to ensure accuracy and consistency. This process is essential for improving AI applications, including image recognition, natural language processing, and autonomous systems. Attention to detail and adherence to instructions are key skills required for this role.

What are the typical daily responsibilities of a data labelling professional?

Data Labelling professionals are generally responsible for reviewing and accurately annotating large volumes of data—such as images, audio, video, or text—to support machine learning and AI projects. This often involves using specialized labeling platforms and following detailed guidelines provided by data scientists or project managers. You may also participate in regular team meetings to discuss quality standards or address ambiguities in data, and your work is typically reviewed for accuracy before being integrated into training datasets. Collaborating with other data annotators, engineers, and analysts is a common part of the process to ensure consistency and high-quality results.

What are the key skills and qualifications needed to thrive in the data labelling position, and why are they important?

To thrive as a Data Labelling professional, you need strong attention to detail, proficiency with data annotation processes, and a basic understanding of machine learning concepts. Familiarity with annotation tools like Labelbox, Supervisely, or Amazon SageMaker Ground Truth is often required, and some roles may value certifications in data processing or AI fundamentals. Reliability, patience, and the ability to follow precise instructions are important soft skills for success in this position. These skills ensure accurate and consistent data labeling, which is critical for developing effective AI models and maintaining data integrity.

How can I get started in data labeling?

To start in data labeling, gain familiarity with annotation tools and understand the specific data types you'll work with, such as images, text, or audio. Building attention to detail and basic knowledge of machine learning concepts can improve your effectiveness; some roles may require basic computer skills or certifications. Entry-level positions often offer flexible schedules and remote work options.

How much do data labelers make?

Data labelers typically earn between $10 and $20 per hour, depending on experience, complexity of tasks, and the platform they work for. Some may earn higher rates with specialized skills or certifications, especially for complex data annotation tasks involving images, videos, or audio. Pay can vary based on whether the work is freelance, part-time, or full-time, and some roles offer project-based or hourly compensation.

Is data labelling a good career?

Data labelling is a common entry-level role in data annotation and machine learning workflows, often requiring attention to detail and familiarity with labeling tools. It can provide opportunities to develop skills in data management and AI, but typically offers lower pay and limited advancement without additional training or experience.

What are data labeling jobs?

Data labeling jobs involve annotating or tagging data such as images, text, or videos to help machine learning models learn and improve. These roles typically require attention to detail and familiarity with labeling tools or software, and they are often performed remotely with flexible schedules.

What are the most commonly searched types of Data Labelling jobs in Washington, DC?

The most popular types of Data Labelling jobs in Washington, DC are:

What are popular job titles related to Data Labelling jobs in Washington, DC?

For Data Labelling jobs in Washington, DC, the most frequently searched job titles are:

What job categories do people searching Data Labelling jobs in Washington, DC look for?

The top searched job categories for Data Labelling jobs in Washington, DC are:

Infographic showing various Data Labelling job openings in Washington, DC as of August 2026, with employment types broken down into 83% Full Time, and 17% Part Time. Highlights an 83% In-person, and 17% Remote job distribution, with an average salary of $186,899 per year, or $89.9 per hour.

Data Scientist

Unissant

Ashburn, VA • On-site

$99K - $164K/yr

Full-time

Re-posted 2 days ago


Job description

Unissant, Inc. delivers innovative capabilities to the agencies that keep our nation healthy and safe. We apply our domain expertise, data acumen, and technology know-how to achieve breakthrough results for our clients. Working collaboratively, we advance missions and careers through a focus on honesty, integrity, and dependability. We continuously look for talent, excited to join that effort. To learn more about our exciting organization, please visit us at www.unissant.com.We are seeking a Data Scientist to join our team and support our client in Ashburn, VA. The ideal candidate will bring experience applying computer vision, image analysis, statistical analysis, machine learning, and data modeling techniques to solve complex mission and business challenges. This role is well suited for a hands-on analytical professional who can work with image, biometric, transactional, and related datasets; build and evaluate image-analysis and predictive models; and communicate insights that support informed decision-making in an Agile team environment.Essential Duties and Responsibilities:Perform hands-on data analysis to support the development of image-analysis models, predictive models, visual analytics, and reporting solutions.Extract, clean, transform, label, annotate, and interpret image, biometric, transactional, and related datasets within a defined problem space to support model development and analytical reporting.Apply computer vision, statistical, and machine-learning techniques to design, train, evaluate, fine-tune, and deploy models that inform mission decisions.Apply image-analysis techniques such as image classification, object detection, image segmentation, image matching, feature extraction, face detection, facial verification, image-quality analysis, or related computer-vision capabilities.Explore and compare a variety of modeling tools, methods, and programming languages to identify high-performing analytical and image-analysis approaches.Support exploratory data analysis, feature development, image-data preparation, annotation, training-set construction, model evaluation, and model-improvement activities.Assess model performance, including false positives, false negatives, model bias, data-quality issues, and operational limitations; recommend improvements as needed.Work collaboratively within a large Agile development team.Work Experience and Job Skills:Two (2) or more years of experience in data science, computer vision, image analysis, advanced analytics, machine learning, biometrics, or related technical work is required.Experience developing, training, fine-tuning, evaluating, or deploying machine-learning or deep-learning models for computer vision, image analysis, or related capabilities.Experience with image classification, object detection, image segmentation, image matching, facial recognition, facial verification, image quality, liveness detection, or similar image-analysis techniques is strongly preferred.Familiarity with biometric technologies, biometric data, identity verification, facial recognition, fingerprints, iris recognition, liveness detection, image matching, or image-quality assessment is strongly preferred.Experience developing machine-learning models and applying advanced analytics techniques to solve complex mission or business problems.Proficiency with programming languages such as Python, R, Scala, or Java; Python experience with computer-vision or machine-learning libraries is strongly preferred.Experience with AI/ML, computer-vision, or deep-learning frameworks and libraries such as PyTorch, TensorFlow, Keras, OpenCV, scikit-learn, YOLO, Detectron, or equivalent platforms.Strong SQL programming skills and experience constructing queries to extract and prepare data for exploratory analysis, image-data processing, and model development.Experience with statistical software and analytical tools such as SAS, SPSS Modeler, R, WEKA, Jupyter, or equivalent platforms.Experience with pattern recognition, automated classification, image categorization, feature extraction, similarity matching, and data categorization techniques.Experience with entity resolution methods, including record linkage, named-entity matching, deduplication, disambiguation, identity matching, or biometric matching.Familiarity with supervised and unsupervised machine-learning techniques and methods.Experience performing data mining, data analysis, image-data preparation, labeling or annotation, and training-set construction.Familiarity with model-performance evaluation methods, such as precision, recall, F1 score, ROC-AUC, confusion matrices, mean average precision, false-match rate, false-non-match rate, or equivalent measures.Strong analytical thinking, problem-solving skills, and attention to detail.Ability to communicate findings effectively to both technical and non-technical audiences.Education:Bachelor's Degree in Mathematics, Statistics, Computer Science, Engineering, Data Science, Artificial Intelligence, Computer Vision, or another related technical field is required.Equivalent practical experience may be considered based on client standards.Advanced degree in a relevant analytical or technical discipline is preferred.Certificates, Licenses and Registrations:Relevant certifications in analytics, machine learning, computer vision, cloud platforms, data science, or related technologies are a plus.Additional technical certifications may be considered based on program needs.Communication Skills:Excellent verbal and written communication skills, including the ability to explain complex analytical and image-analysis findings clearly and effectively.Strong collaboration skills and the ability to work across technical and business stakeholders.Clearance Requirements:Ability to obtain and maintain a Public Trust position and favorable suitability determination based on a CBP background investigation is required.U.S. citizenship is required due to client and suitability requirements.Prior DHS, CBP, federal, law-enforcement, biometric, identity-management, or similarly regulated-environment experience is preferred.Travel:This is a hybrid position based in Ashburn, VA, with onsite support expected one to two days per week and additional onsite presence as required by mission needs.Environmental Requirements:Mainly a routine office environment.
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