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Annotation Math Jobs in Ashburn, VA (NOW HIRING)

Varsity Tutors

TACHS Tutor

Rockville, MD · Remote

$40/hr

Skilled at teaching reading passage annotation, grammar rule application, and mental math estimation strategies for TACHS. Guides students through vocabulary-in-context questions, paragraph ...

Varsity Tutors

TACHS Tutor

Fairfax, VA · Remote

$40/hr

Skilled at teaching reading passage annotation, grammar rule application, and mental math estimation strategies for TACHS. Guides students through vocabulary-in-context questions, paragraph ...

Varsity Tutors

TACHS Tutor

Washington, DC · Remote

$40/hr

Skilled at teaching reading passage annotation, grammar rule application, and mental math estimation strategies for TACHS. Guides students through vocabulary-in-context questions, paragraph ...

Varsity Tutors

TACHS Tutor

Leesburg, VA · Remote

$40/hr

Skilled at teaching reading passage annotation, grammar rule application, and mental math estimation strategies for TACHS. Guides students through vocabulary-in-context questions, paragraph ...

Varsity Tutors

ISEE- Lower Level Tutor

Fairfax, VA · Remote

$40/hr

... and Mathematics Achievement covering arithmetic, basic geometry, and pre-algebra for students ... Guides students through reading passage annotation, word relationship identification, multi-step ...

Varsity Tutors

ISEE- Lower Level Tutor

Rockville, MD · Remote

$40/hr

... and Mathematics Achievement covering arithmetic, basic geometry, and pre-algebra for students ... Guides students through reading passage annotation, word relationship identification, multi-step ...

Varsity Tutors

ISEE- Lower Level Tutor

Leesburg, VA · Remote

$40/hr

... and Mathematics Achievement covering arithmetic, basic geometry, and pre-algebra for students ... Guides students through reading passage annotation, word relationship identification, multi-step ...

Varsity Tutors

ISEE- Lower Level Tutor

Washington, DC · Remote

$40/hr

... and Mathematics Achievement covering arithmetic, basic geometry, and pre-algebra for students ... Guides students through reading passage annotation, word relationship identification, multi-step ...

BlackSky

Staff Engineer, AI

Herndon, VA · On-site +1

Collaborate with the Data QA team to define annotation standards, resolve taxonomy issues, and ... Bachelor's degree in CS/EE/math/statistics or a related quantitative field. * Strong proficiency in ...

BlackSky

Staff Engineer, AI

Herndon, VA · On-site

Collaborate with the Data QA team to define annotation standards, resolve taxonomy issues, and ... Bachelor's degree in CS/EE/math/statistics or a related quantitative field. * Strong proficiency in ...

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All JobsAnnotation Math JobsAnnotation Math Jobs in Ashburn, VA

Annotation Math information

See Ashburn, VA salary details

$23K

$60.2K

$96.6K

How much do annotation math jobs pay per year?

As of Jun 11, 2026, the average yearly pay for annotation math in Ashburn, VA is $60,167.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,000.00 and $71,600.00 per year, depending on experience, location, and employer.

Does the FBI hire mathematicians?

Yes, the FBI hires mathematicians for roles in cryptography, data analysis, and intelligence analysis. These positions often require strong analytical skills, a background in mathematics or related fields, and security clearances. Mathematicians at the FBI may work with specialized tools and require relevant certifications or education levels.

What is the highest paid math job?

The highest paid math jobs typically include roles such as quantitative analysts, data scientists, and actuarial directors, often found in finance, technology, and insurance industries. These positions require advanced skills in statistics, programming, and data analysis, and they can offer salaries exceeding $150,000 annually depending on experience and location.

What is the difference between Annotation Math vs Data Annotator?

AspectAnnotation MathData Annotator
Required CredentialsBasic education, sometimes specialized training in annotation toolsHigh school diploma or equivalent, on-the-job training
Work EnvironmentData labeling teams, tech companies, remote or onsiteData labeling teams, tech companies, remote or onsite
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Common Search IntentUnderstanding roles related to data annotation and mathComparing data annotation jobs

Annotation Math and Data Annotator roles both involve data labeling within AI and machine learning industries. Annotation Math may focus more on mathematical annotations, while Data Annotator generally covers broader data labeling tasks. Both roles often share similar work environments and required skills, making them closely related in the data annotation field.

What are Annotation Math jobs?

Annotation Math jobs involve labeling, tagging, and categorizing mathematical data, such as equations, formulas, graphs, or written math problems, to create high-quality datasets. These annotated datasets are often used to train artificial intelligence (AI) and machine learning models to recognize and process mathematical content accurately. Annotation Math professionals need a strong understanding of mathematics, attention to detail, and familiarity with annotation tools or platforms. This work is critical for improving technologies like automated math solvers, educational apps, and document digitization.

What are the key skills and qualifications needed to thrive as an Annotation Math Specialist, and why are they important?

To thrive as an Annotation Math Specialist, you need a solid understanding of mathematics, attention to detail, and familiarity with educational or assessment standards, often supported by a relevant degree. Proficiency with annotation tools, data labeling platforms, and sometimes LaTeX or similar mathematical typesetting systems is typically required. Strong analytical thinking, communication, and the ability to work independently are essential soft skills for accuracy and consistency. These skills and qualities are crucial to ensure high-quality, precise annotations that support machine learning, educational resources, or assessment development.

How much does data annotation pay for math?

Data annotation jobs for math typically pay between $10 and $20 per hour, depending on the complexity of the tasks and the employer. Rates can vary based on experience, the platform used, and whether the work is freelance or full-time, with some specialized roles offering higher compensation for advanced skills in math or data labeling tools.

Is data annotation a good career?

Data annotation for roles like annotation math involves labeling data to train machine learning models, often requiring attention to detail and familiarity with tools like annotation platforms. It can offer flexible schedules and entry-level opportunities but may have variable pay and limited advancement without additional skills or certifications.

What are some common challenges faced by professionals in Annotation Math roles, and how can they be addressed?

Professionals in Annotation Math roles often encounter challenges such as interpreting ambiguous mathematical data, maintaining consistency in labeling complex equations, and managing repetitive tasks that require high attention to detail. Addressing these challenges involves following clear annotation guidelines, collaborating with team members to resolve uncertainties, and utilizing quality assurance tools to minimize errors. Regular feedback sessions and ongoing training also help ensure accuracy and support professional growth in this specialized field.
What are popular job titles related to Annotation Math jobs in Ashburn, VA? For Annotation Math jobs in Ashburn, VA, the most frequently searched job titles are:
What job categories do people searching Annotation Math jobs in Ashburn, VA look for? The top searched job categories for Annotation Math jobs in Ashburn, VA are:
What cities near Ashburn, VA are hiring for Annotation Math jobs? Cities near Ashburn, VA with the most Annotation Math job openings:
Annotation Math jobs near you
Assistant Research Scientist (PREP0004176)

Assistant Research Scientist (PREP0004176)

Johns Hopkins University

Gaithersburg, MD • On-site

Full-time

Posted 3 days ago

Johns Hopkins Medicine rating

7.5

Company rating: 7.5 out of 10

Based on 200 frontline employees who took The Breakroom Quiz

225th of 870 rated healthcare providers

Job description

Description
PREP Research Associate
This position is part of the National Institute of Standards and Technology (NIST) Professional Research Experience Program (PREP). NIST recognizes that its research staff may want to collaborate with researchers at academic institutions on specific projects of mutual interest and, therefore, requires those institutions to be recipients of a PREP award. The PREP program involves staff from a wide range of backgrounds conducting scientific research across various fields. Individuals in this position will perform technical work supporting the collaboration's scientific research.
Research Title:
Reliability of Human and LLM Annotations for AI Risk Assessment
The work will entail:
This project focuses on using Large Language Models (LLMs) to provide annotations of evaluation data (a.k.a., LLM as judge), and the design of an Inter-Annotator Agreement study to assess the reliability of both human and LLM annotations. The candidate will explore assessing the indicators of a given AI-related risk, determining how to identify them, and providing annotators with examples to annotate the presence of various risks. The project aims to develop an annotation framework for AI risk assessment and establish metrics for data quality in AI risk research, supporting broader work at NIST in assessing and measuring the validity and reliability of AI-related risks in data annotation.
U.S. Citizen Preferred
Key responsibilities will include but are not limited to:
  • Gain familiarity with existing literature on data annotation and LLM as judge
  • Understand NIST's role and ongoing efforts in assessing and measuring the validity and reliability of AI-related risks in data annotation
  • Contribute to developing an annotation framework for AI risk assessment
  • Collaborate effectively with cross-functional and interdisciplinary stakeholders to ensure successful project outcomes

Deliverables
  • Contributions to a NIST report that supports ongoing NIST AI evaluation efforts focused on the design of an Inter-Annotator Agreement to assess the reliability of both human and LLM annotations.

Qualifications
  • Background in Computer Science, Data Science, or related field.
  • Education level: Bachelor's or Graduate Degree
  • Strong interest in data annotation and AI risks
  • Familiarity with scientific reading and technical writing

Application Instructions
Please upload the following with your application:
• CV/Resume
*Please limit C.V to 3 pages only and ONLY include a valid email address for your contact info. Your resume will not be considered if the following information is included on your CV/resume.
• Self portraits
• Phone number
• Home address/Country
• Citizenship status
• Languages spoken
• Sex/Gender
Privacy Act Statement
Authority: 15 U.S.C. § 278g-1(e)(1) and (e)(3) and 15 U.S.C. § 272(b) and (c)
Purpose: The National Institute for Standards and Technology (NIST) hosts the Professional Research Experience Program (PREP) which is designed to provide valuable laboratory experience and financial assistance to undergraduates, post-bachelor's degree holders, graduate students, master's degree holders, postdocs, and faculty.
PREP is a 5-year cooperative agreement between NIST laboratories and participating PREP Universities to establish a collaborative research relationship between NIST and U.S. institutions of higher education in the following disciplines including (but may not be limited to) biochemistry, biological sciences, chemistry, computer science, engineering, electronics, materials science, mathematics, nanoscale science, neutron science, physical science, physics, and statistics. This collection of information is needed to facilitate administrative functions of the PREP Program.
Routine Uses: NIST will use the information collected to perform the requisite reviews of the applications to determine eligibility, and to meet programmatic requirements. Disclosure of this information is also subject to all the published routine uses as identified in the Privacy Act System of Records Notices: NIST-1: NIST Associates.
Disclosure: Furnishing this information is voluntary. When you submit the form, you are indicating your voluntary consent for NIST to use of the information you submit for the purpose stated.

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