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Remote Data Annotation Analyst Jobs in Virginia (NOW HIRING)

Maximus

Data Scientist (Remote)

VA · On-site +1

General information Job Posting Title Data Scientist (Remote) Date Tuesday, August 4, 2026 City ... This position applies advanced analytics, statistical methods, and data visualization to improve ...

Staffed4U

Biologicial Data Analyst

Chantilly, VA · On-site +1

Hybrid Work Environment with remote and onsite work flexibility based on program requirements ... data analysis. You'll have the opportunity to work alongside experts in computational science ...

Staffed4U

Chemical Data Analyst

Chantilly, VA · On-site +1

Hybrid Work Environment with remote and onsite work flexibility based on program requirements ... data analysis. You'll have the opportunity to work alongside experts in computational science ...

Maximus

Data Scientist II (Remote)

VA · On-site +1

General information Job Posting Title Data Scientist II (Remote) Date Tuesday, August 4, 2026 City ... This role applies advanced analytics and research methods to help improve the short- and long-term ...

Parsons

Data Analytics Architect

Alexandria, VA · On-site +1

The Data Analytics Architect leads the design, integration, and governance of data systems that ... FAA Part 107 Remote Pilot Certification (required) Physical Requirements / Working Conditions ...

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Remote Data Annotation Analyst information

What is a remote data annotation analyst?

Remote Data Annotation Analysts are professionals who label, categorize, or tag data—such as images, text, audio, or video—from a remote location. Their work helps train machine learning algorithms by providing structured datasets that computers can learn from. These analysts use specialized tools to identify relevant features in raw data, ensuring accuracy and consistency. The role often requires attention to detail, basic technical skills, and the ability to follow specific guidelines or instructions. This position is commonly found in industries like artificial intelligence, autonomous vehicles, and natural language processing.

What are the key skills and qualifications needed to thrive as a remote data annotation analyst?

To thrive as a Remote Data Annotation Analyst, you need strong attention to detail, analytical thinking, and a high school diploma or equivalent, with many roles preferring experience in data-related tasks. Familiarity with data annotation platforms (like Labelbox or AWS SageMaker Ground Truth) and basic understanding of data management tools are typically required. Excellent time management, self-motivation, and clear communication help analysts manage remote workloads and collaborate effectively with distributed teams. These skills ensure accurate, high-quality annotated data essential for training and validating machine learning models.

How does a remote data annotation analyst typically collaborate with team members and ensure consistent labeling standards?

As a Remote Data Annotation Analyst, you’ll frequently work within a distributed team, using collaboration tools such as Slack, project management platforms, and shared annotation guidelines. Regular virtual meetings and feedback sessions help ensure everyone applies labeling standards consistently and resolves ambiguities. It’s common to review peer annotations and participate in quality assurance checks, promoting a culture of accuracy and continuous improvement. Clear communication and attention to detail are essential for maintaining high-quality annotated datasets across the team.

What is the difference between Remote Data Annotation Analyst vs Remote Data Labeler?

AspectRemote Data Annotation AnalystRemote Data Labeler
Required CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentHome-based, flexible hoursHome-based, flexible hours
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Job FocusAnalyzing and verifying labeled data, quality controlLabeling data, annotating images, text, or audio

The main difference is that Remote Data Annotation Analysts focus on verifying and ensuring the quality of labeled data, often involving analysis and review, while Remote Data Labelers primarily perform the task of labeling or annotating raw data. Both roles are essential in AI development and share similar work environments and skill requirements, but their specific responsibilities differ in scope and focus.

What are the most commonly searched types of Data Annotation Analyst jobs in Virginia?

The most popular types of Data Annotation Analyst jobs in Virginia are:

What are popular job titles related to Remote Data Annotation Analyst jobs in Virginia?

For Remote Data Annotation Analyst jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Remote Data Annotation Analyst jobs in Virginia look for?

The top searched job categories for Remote Data Annotation Analyst jobs in Virginia are:

What cities in Virginia are hiring for Remote Data Annotation Analyst jobs?

Cities in Virginia with the most Remote Data Annotation Analyst job openings:

Remote Data Annotation Analyst jobs near you
Infographic showing various Remote Data Annotation Analyst job openings in Virginia as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 19% Part Time, and 2% Contract. Highlights an 85% Physical, 4% Hybrid, and 11% Remote job distribution.

Software Engineer, II - Autonomy Data

Torc Robotics

Blacksburg, VA • On-site, Remote

$100K - $120K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 16 days ago

Job description

About The Company:
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet The Team:
Torc is hiring an Autonomy Data Engineer Level 2 to help design, build and operate the data infrastructure that powers our autonomy program. You will build the pipelines, storage systems, and tooling that turn raw vehicle sensor logs into the curated, structured datasets that our perception, planning and simulation engineers depend on.
This is a high-ownership role on a lean team. Moving large scale sensor data reliably from vehicles operating in demanding environments and making it quickly available for model training is a difficult and high-impact problem to solve.
What You'll Do:
  • Data Lake and Ingestion Pipeline
    • Contribute to the design and organization of the program's data lake, including schema definitions, partitioning strategy and metadata indexing.
    • Build and maintain end-to-end pipelines that ingest high-bandwidth sensor logs from vehicles into cloud storage with high reliability and tolerant of ad-hoc and intermittent connectivity mechanisms.
    • Implement data validation and integrity checks that can detect corrupted information, missing sensors, and inconsistent calibration prior to the data being processed by downstream systems.
    • Implement retention, tiering and lifecycle policies for data to balance storage costs with development value.
  • Dataset Curation and Labeling Infrastructure
    • Build tooling to query raw logs to produce curated training and evaluation datasets.
    • Build automation to run cost-effective pseudo-labeling workflows at the scale of data ingest.
    • Implement data quality and model performance metrics that are used to direct labeling effort toward the highest-value examples.
  • Autonomy Data Visualization
    • Deploy and maintain data visualization tooling to support log review, annotation QA, and autonomy debugging workflows.
    • Build integrations between the visualization tooling and the data lake so engineers can navigate from a dataset entry or model failure directly to the origin log data
    • Work with autonomy engineers to define and surface custom visualization panels and implement metrics for analyzing unstructured operating environments.
    • Build dashboards that provide the autonomy engineers visibility into data coverage by terrain type, operating environment and geographic region.
  • Cross-functional Collaboration
    • Establish and document data contracts between the data services and model training consumers.
    • Partner with perception, planning and embedded engineers across the data lifecyle: from shaping the logging schemas and collection triggers to defining the dataset interfaces that supply model training and evaluation.
    • Follow and help evolve data engineering standards, best practices, and tooling choices for an innovative and fast-paced team.
    • Contribute to the data roadmap and surface findings to senior technical leadership.

What You'll Need to Succeed:
  • Bachelor's degree in Computer Science, Computer Engineering, Software Engineering, Electrical Engineering or a related field with 4+ years of data engineering experience or a Master's with 2+ years.
  • Strong proficiency in Python and SQL, with demonstrated ability to build production-quality data pipelines
  • Experience with cloud data infrastructure (AWS preferred: S3, Glue Athena, redshift, or equivalent) and infrastructure-as-code tools (Terraform, Cloud Formation).
  • Solid understanding of data partitioning strategies and columnar storage formats (Parquet, Orc, etc.)
  • Experience building and operating data pipelines that process time-series and binary data.
  • Proven ability to evaluate and integrate open-source tooling when appropriate versus building from scratch.
  • Good instincts for delivering data quality through first-class implementations of monitoring, validation and lineage tracking.

Bonus points!
  • Experience with autonomous vehicles, robotics, or other sensor-driven autonomous systems.
  • Deep experience with Foxglove or Rerun beyond basic playback, e.g. building custom extensions or integrating them into a structured log review or annotation QA workflow.
  • Familiarity with the MCAP CLI and/or python library and experience converting MCAP data to columnar data formats for further querying and processing.
  • Experience with data curation for ML training, e.g. diversity sampling, pseudo-labeling, and dataset versioning.

U.S. Citizenship Requirement:
This position requires access to information and systems that are restricted under U.S. law. Accordingly, only U.S. citizens are eligible for this role. This requirement is based on applicable government regulations and is not related to immigration status discrimination.
Perks of Being a Full-time Torc'r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer match
  • Flexibility in schedule and generous paid vacation (available immediately after start date)
  • Company-wide holiday office closures
  • AD+D and Life Insurance

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.
Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: R-102913
Hiring Range for Job Opening
US Pay Range
$139,000-$166,800 USD

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