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Remote Data Annotation Analyst Jobs in San Angelo, TX

Remote micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety ... safety data analysis. * Expertise in reconciling aggregate safety data and identifying ...

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

Remote micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a ... missing data handling in alignment with the statistical analysis plan (SAP). * Identify ...

Biostatistician

San Angelo, TX · Remote

$60 - $65/hr

Remote micro1 is engaging Biostatisticians to contribute their clinical statistics expertise to a ... missing data handling in alignment with the statistical analysis plan (SAP). * Identify ...

Enjoy the flexibility of remote work and the freedom to set your own schedule. This is an ... Proficient in financial analysis, financial modeling, data analysis, and other reasoning exercises ...

Remote micro1 is engaging Biostatisticians to contribute to a customer's advanced project in AI ... Source, construct, and curate authentic datasets including trial data, patient records, and ...

Biostatistician

San Angelo, TX · Remote

$60 - $100/hr

Remote micro1 is engaging Biostatisticians to contribute to a customer's advanced project in AI ... Source, construct, and curate authentic datasets including trial data, patient records, and ...

Showing results 21-32

Remote Data Annotation Analyst information

See San Angelo, TX salary details

$32.8K

$79.6K

$131K

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

As of Aug 16, 2026, the average yearly pay for remote data annotation analyst in San Angelo, TX is $79,609.00, according to ZipRecruiter salary data. Most workers in this role earn between $60,200.00 and $93,400.00 per year, depending on experience, location, and employer.

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 popular job titles related to Remote Data Annotation Analyst jobs in San Angelo, TX?

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

What job categories do people searching Remote Data Annotation Analyst jobs in San Angelo, TX look for?

The top searched job categories for Remote Data Annotation Analyst jobs in San Angelo, TX are:

What cities near San Angelo, TX are hiring for Remote Data Annotation Analyst jobs?

Cities near San Angelo, TX with the most Remote Data Annotation Analyst job openings:

Infographic showing various Remote Data Annotation Analyst job openings in San Angelo, TX as of June 2026, with employment types broken down into 57% Full Time, 30% Part Time, 3% Temporary, 7% Contract, and 3% Nights. Highlights an 90% Physical, 2% Hybrid, and 8% Remote job distribution, with an average salary of $79,609 per year, or $38.3 per hour.

Clinical Pharmacy Technicians

micro1 AI

San Angelo, TX • Remote

$70 - $80/hr

Part-time

Posted 12 days ago


Job description

Role Title: Pharmacovigilance Expert


Role Type: Contractor


Location: Remote


micro1 is engaging Pharmacovigilance Experts to contribute their advanced drug safety expertise on a key customer project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. This opportunity is ideal for professionals experienced in authoring and reviewing complex safety reports, passionate about data quality, and committed to clear written and verbal communication.


Scope of Work

  1. Author and review evaluation tasks based on DSURs, PSURs/PBRERs, and associated safety data and case-level records.
  2. Apply expert judgment to assess the accuracy and adequacy of interval safety findings, signal evaluations, and benefit-risk conclusions in alignment with best practices.
  3. Assess template and structural conformity to ICH E2F and ICH E2C requirements, including proper section content, presentation of cumulative versus interval data, and completeness of appendices.
  4. Reconcile figures and case counts across report sections and data sources, identifying and documenting discrepancies significant for regulatory review.
  5. Evaluate safety conclusions in light of new data or events, and provide clear, structured written rationales supporting your determinations.
  6. Deliver structured feedback to inform the development of AI-driven tools for pharmacovigilance documentation and analysis.


Preferred Qualifications

  1. 5+ years of pharmacovigilance or drug safety experience at a sponsor, CRO, or as an independent consultant.
  2. Demonstrated proficiency in authoring or reviewing DSURs and/or PSURs/PBRERs from start to finish.
  3. Working fluency with ICH E2F, ICH E2C(R2), and GVP guidelines, including signal management and benefit-risk assessment methodology.
  4. Hands-on experience with MedDRA coding, seriousness and causality assessment, expectedness determination, and aggregate safety data analysis.
  5. Expertise in reconciling aggregate safety data and identifying inconsistencies with case-level information.
  6. Advanced degree in life sciences, pharmacy, nursing, or medicine (PharmD, MD, MSc, or equivalent).
  7. Experience in both development-stage and post-marketing safety reporting, QPPV or deputy QPPV roles, safety committee participation, or AI-assisted safety review tools is a plus.