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Flexible Data Annotation Analyst Jobs (NOW HIRING)

Sr. Software Analyst, Data, Autonomy

Palo Alto, CA · On-site

$101K - $127K/yr

Analyze large‑scale 2D/3D annotation datasets to identify data gaps, quality issues, coverage ... gaps, and inefficiencies impacting Perception and ML training. * Utilize dashboards and reports to ...

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Quality Assurance and Analysis: * Conduct manual quality analysis of model results. * Recognize ...

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Quality Assurance and Analysis: * Conduct manual quality analysis of model results. * Recognize ...

The ideal candidate will have a foundational understanding of machine learning, data annotation ... Quality Assurance and Analysis: * Conduct manual quality analysis of model results. * Recognize ...

Manage the end-to-end data annotation process * Analyze data quality metrics (accuracy, consistency, coverage, and diversity) and turn findings into actionable recommendations * Implement approved ...

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Flexible Data Annotation Analyst information

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$34K

$82.6K

$136K

How much do flexible data annotation analyst jobs pay per year?

As of Sep 13, 2026, the average yearly pay for flexible data annotation analyst in the United States is $82,640.00, according to ZipRecruiter salary data. Most workers in this role earn between $62,500.00 and $97,000.00 per year, depending on experience, location, and employer.

What is a flexible data annotation analyst?

A Flexible Data Annotation Analyst is a professional responsible for labeling, categorizing, and tagging data—such as text, images, audio, or video—to prepare it for use in machine learning and artificial intelligence projects. The 'flexible' aspect typically means the role allows for remote work, adjustable hours, or project-based assignments. Analysts use specific tools and follow detailed guidelines to ensure data quality and consistency. This role is crucial for training accurate AI models, as well-annotated data helps improve the performance of automated systems.

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

To thrive as a Flexible Data Annotation Analyst, you need keen attention to detail, analytical thinking, and a basic understanding of data labeling processes, often supported by a high school diploma or relevant experience. Familiarity with annotation tools such as Labelbox, Prodigy, or similar platforms, as well as basic proficiency in spreadsheet software, is typically required. Strong time management, adaptability, and clear communication skills help you deliver accurate results and work effectively with remote teams. These abilities ensure high-quality, consistent data labeling that is critical for training reliable machine learning models.

How does a flexible data annotation analyst typically collaborate with other teams to ensure data quality?

As a Flexible Data Annotation Analyst, you will frequently interact with data scientists, machine learning engineers, and project managers to clarify annotation guidelines and resolve ambiguities in the data. Collaboration often involves participating in virtual meetings, providing feedback on annotation tools, and reporting inconsistencies or uncertainties encountered during the labeling process. This teamwork ensures that annotated datasets meet project standards and contribute to high-quality machine learning outcomes. Regular communication and openness to feedback are key to success in this collaborative environment.

Can I work as a flexible data annotation analyst with no experience?

Flexible data annotation analyst roles often do not require prior experience, as training is typically provided to teach the necessary skills and tools. Basic computer literacy and attention to detail are usually sufficient to start, making it accessible for beginners interested in data labeling tasks.

Do data annotation jobs offer flexible hours?

Data annotation jobs often offer flexible hours, allowing workers to choose when they complete tasks, especially in freelance or remote roles. However, some positions may have deadlines or specific schedules depending on the employer or project requirements.

Does data annotation actually pay well?

Data annotation analysts typically earn hourly wages that are close to minimum wage or slightly above, depending on the platform and complexity of tasks. Pay rates can vary based on experience, skill level, and the employer, but generally, it is not considered a high-paying role. Many positions are freelance or part-time, which can impact overall earnings.

Is it hard to get hired for a flexible data annotation analyst?

Getting hired as a flexible data annotation analyst generally depends on having basic computer skills, attention to detail, and familiarity with annotation tools. Many positions are entry-level and may not require extensive experience, making the role accessible to a wide range of candidates. However, competition can vary based on the employer and location, and some roles may prefer candidates with prior experience or specific technical knowledge.
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Infographic showing various Flexible Data Annotation Analyst job openings in the United States as of September 2026, with employment types broken down into 1% As Needed, 66% Full Time, 30% Part Time, and 3% Contract. Highlights an 87% Physical, 1% Hybrid, and 12% Remote job distribution, with an average salary of $82,640 per year, or $39.7 per hour.

Sr. Software Analyst, Data, Autonomy

Palo Alto, CA • On-site

Rivian
Automobile Dealers • 10K+ employees

$101K - $127K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 25 days ago


Key responsibilities

  • Lead strategic planning and coordination of 3D/2D annotation projects, working with internal and external partners.

  • Manage vendor relationships, ensure quality of deliverables, resolve defects, and facilitate feature enhancements.

  • Conduct quality control on annotated datasets and analyze data insights to identify data gaps, quality issues, and inefficiencies.


Rivian rating

7.3

Company rating: 7.3 out of 10

Based on 160 frontline employees who took The Breakroom Quiz


Job description

About Rivian

Rivian is on a mission to keep the world adventurous forever. This goes for the emissions‑free Electric Adventure Vehicles we build, and the curious, courageous souls we seek to attract.

As a company, we constantly challenge what’s possible, never simply accepting what has always been done. We reframe old problems, seek new solutions and operate comfortably in areas that are unknown. Our backgrounds are diverse, but our team shares a love of the outdoors and a desire to protect it for future generations.

Role Summary

In this role, you will lead strategic planning and coordination of 3D/2D annotation projects, working closely with both internal and external partners. A key responsibility is rigorous vendor management, ensuring the quality of deliverables, resolving defects, and facilitating feature enhancements. The role also encompasses developing policies, setting precise labeling protocols, executing accurate 3D sensor data annotation, and conducting thorough quality control on all generated datasets. You will partner closely with Annotation Operations, Perception, and Engineering teams to ensure data readiness for model training and evaluation. The ideal candidate is data‑driven, detail‑oriented, and execution‑focused, with a strong understanding of annotation workflows and a passion for improving data quality and efficiency at scale. This role plays a critical part in enabling informed decision‑making, continuous process improvement, and scalable annotation operations across internal teams and external vendors.

Responsibilities Analyzing Data Insights
  • Analyze large‑scale 2D/3D annotation datasets to identify data gaps, quality issues, coverage gaps, and inefficiencies impacting Perception and ML training.
  • Utilize dashboards and reports to monitor annotation throughput, efficiency, and cost; quality metrics (QA pass rates, error types, rework); vendor and annotator performance trends.
  • Interpret complex annotation and perception data into clear, actionable insights for engineering, annotation operations, and leadership.
  • Partner with Perception teams to align data readiness metrics with model training and evaluation needs.
  • Effectively communicate data findings to business partners, bridging the gap between technical data and strategic organizational goals.
Annotation Operations & Quality
  • Assess the level of effort for annotation projects and support end‑to‑end execution, including in‑house vs. vendor decisions.
  • Collaborate with stakeholders to gather labeling requirements and define, maintain, and evolve labeling policies.
  • Manage relationships with various vendors, including contract and quote review, for third‑party annotation services and tools.
  • Define and track annotation quality, productivity, and certification metrics; continuously refine benchmarks.
  • Conduct QA/QC analysis on annotated data, identify systemic issues, and provide structured feedback to annotators and vendors.
  • Implement and measure labeling efficiency improvements, using data to validate impact.
Process Improvement & Automation
  • Prepare technical reports and collaborate with cross‑functional engineering teams to ensure consistent process implementation, with the ability to automate basic processes.
  • Identify opportunities to make data delivery and annotation workflows faster, more accurate, and scalable.
  • Identify and propose enhancements to address deficiencies in existing tooling, improving the efficiency and accuracy of annotation workflows.
Cross‑Functional & Vendor Collaboration
  • Work closely with Annotation Ops, Perception, and Engineering teams to ensure consistent process implementation.
  • Support vendor management by analyzing performance, cost, and quality metrics across multiple annotation partners.
  • Prepare technical and operational reports to support planning, execution, and decision‑making.
  • Coordinate across teams and time zones to ensure alignment and timely delivery.
Qualifications Required
  • BS degree in a technical or related field with 2+ years of relevant experience (or 5+ years equivalent industry experience).
  • 2+ years supporting data annotation, ML data, or labeling‑related projects.
  • Strong understanding of 2D/3D data annotation workflows for ML and Perception use cases.
  • Experience with error taxonomy development and quality assurance (QA) frameworks for data annotation.
  • Working knowledge of databases and/or data visualization tools.
  • Experience analyzing LiDAR point clouds, video, and image annotation data.
  • Ability to manage multiple projects, prioritize effectively, and deliver under tight timelines.
  • Strong written and verbal communication skills, with the ability to explain project insights to non‑technical stakeholders.
  • Experience mentoring or guiding junior team members or offshore teams.
Nice to Have
  • Experience building or improving operational analytics for efficiency, cost, or quality.
  • Comfort working in a fast‑paced, cross‑functional, and collaborative environment.
  • Hands‑on experience with data analysis, metrics tracking, and dashboarding.
Pay Disclosure

The salary range for this role is $132,100.00 - $165,100.00 for San Francisco Bay Area based applicants. This is the lowest to highest salary we in good faith believe we would pay for this role at the time of this posting. An employee’s position within the salary range will be based on several factors including, but not limited to, specific competencies, relevant education, qualifications, certifications, experience, skills, geographic location, shift, and organizational needs.

Benefits

We offer a comprehensive package of benefits for full‑time and part‑time employees, their spouse or domestic partner, and children up to age 26, including but not limited to paid vacation, paid sick leave, and a competitive portfolio of insurance benefits including life, medical, dental, vision, short‑term disability insurance, and long‑term disability insurance to eligible employees. You may also have the opportunity to participate in Rivian’s 401(k) Plan and Employee Stock Purchase Program if you meet certain eligibility requirements. Full‑time employee coverage is effective on their first day of employment. Part‑time employee coverage is effective the first of the month following 90 days of employment. More information about benefits is available at rivianbenefits.com.

Equal Opportunity

Rivian is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition or any other characteristic protected by law.

Rivian is committed to ensuring that our hiring process is accessible for persons with disabilities. If you have a disability or limitation, such as those covered by the Americans with Disabilities Act, that requires accommodations to assist you in the search and application process, please email us at candidateaccommodations@rivian.com.

Candidate Data Privacy

Rivian may collect, use and disclose your personal information or personal data when you apply for employment and/or participate in our recruitment processes. This data includes contact, demographic, communications, educational, professional, employment, social media/website, network/device, recruiting system usage/interaction, security and preference information. Rivian may use your Candidate Personal Data for the purposes of tracking interactions with our recruiting system; carrying out, analyzing and improving our application, recruitment process; establishing an employment relationship; complying with legal, regulatory and corporate governance obligations; recordkeeping; ensuring network and information security and preventing fraud; and other required or permitted uses under applicable law.

Rivian may share your Candidate Personal Data with internal personnel, Rivian affiliates and service providers such as background checks and staffing services. Rivian may transfer or store internationally your Candidate Personal Data in the United States, Canada, the United Kingdom, the European Union and in the cloud.

Please note that we are currently not accepting applications from third party application services.

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About Rivian

Sourced by ZipRecruiter

Rivian is a pioneering automotive industry player headquartered in Irvine, California. Established in 2009, the company has made notable advancements in developing sustainable transportation solutions. It is widely recognized for its electric adventure vehicles: the R1T pickup and the R1S SUV. Rivian is dedicated to creating a positive shift in societal mobility and emphasizes sustainability, innovation, and adventure as part of its core values. Their mission is to keep the world adventurous forever - a testament to their commitment in transitioning the world to sustainable transportation. Rivian's achievements are numerous, with one of the most notable being securing a significant multi-billion dollar investment from Amazon for the production of electric delivery vans.

Industry

Automobile dealers

Company size

10,000+ Employees

Headquarters location

Irvine, CA, US

Year founded

2009