Mathematics QA Lead - Remote
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Key skills for this role
About the Role
YO IT Consulting is hiring a Mathematics Quality Assurance Lead for a remote contract role. You will oversee quality and consistency in mathematics AI training projects, review AI-generated math content, and provide feedback.
Key Skills for This Role
Responsibilities
- Quality monitoring: Spot check mathematics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues
- Mathematical review: Evaluate AI generated math explanations, proofs, derivations, calculations, word problem solutions, diagrams/descriptions, and step by step reasoning for correctness and clarity
- Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and math specific review standards
- Question handling: Respond to trainer/QA questions clearly and promptly, especially around reasoning validity, notation, assumptions, solution methods, proof structure, formatting, and rubric interpretation
- Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow ups, and flag availability issues when needed
- Documentation: Create and maintain mathematics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials
- Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and mathematics specific review requirements
- Quality alignment: Ensure all trainers and QAs apply mathematics guidelines consistently and understand updates as projects evolve
- Error pattern analysis: Identify recurring issues such as skipped reasoning steps, invalid simplifications, wrong formulas, notation inconsistencies, arithmetic mistakes, or answers that are correct but poorly justified
- Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for mathematics AI training projects
Requirements
- Bachelor's, Master's, or PhD degree in Mathematics, Applied Mathematics, Statistics, Physics, Engineering, Computer Science, Mathematics Education, or a closely related quantitative field
- Strong grasp of the English language
- 3+ years of professional experience in mathematics, teaching, tutoring, research, quantitative analysis, technical writing, curriculum development, problem creation, assessment design, or math content review
- Strong understanding of core mathematics topics such as algebra, geometry, trigonometry, calculus, linear algebra, discrete mathematics, probability, statistics, number theory, combinatorics, differential equations, and mathematical proofs
- Ability to evaluate math content against detailed rubrics
- Comfortable reviewing both conceptual explanations and step by step solutions
- Familiarity with mathematical tools or workflows such as LaTeX, Python, MATLAB, R, WolframAlpha/Mathematica, GeoGebra, Desmos, spreadsheet modeling, or symbolic computation tools is preferred
- Experience leading or supporting remote teams of trainers, annotators, reviewers, educators, technical writers, or QAs is strongly preferred
- Comfortable working in fast moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems
- Highly detail oriented and organized
- Experience with AI training, data annotation, large language models, prompt/response evaluation, mathematical content QA, or rubric based LLM evaluation is a strong plus
Full Job Posting
Job Description
- Job Title: Mathematics Quality Assurance Lead
- Job Type: Contract
- Location: Remote
- In this hourly, remote contractor role, you will work as a Mathematics Quality Assurance Lead to oversee quality, consistency, and trainer performance across mathematics AI training projects.
- You will review AI generated math content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards.
- You will assess work for mathematical accuracy, logical reasoning, calculation correctness, proof validity, notation quality, clarity, formatting, instruction following, and adherence to project specific rubrics.
- You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently.
- This role requires strong mathematics expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote technical teams.
- Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise.
Your Profile
- Bachelor’s, Master’s, or PhD degree in Mathematics, Applied Mathematics, Statistics, Physics, Engineering, Computer Science, Mathematics Education, or a closely related quantitative field.
- Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear mathematical feedback in English.
- 3+ years of professional experience in mathematics, teaching, tutoring, research, quantitative analysis, technical writing, curriculum development, problem creation, assessment design, or math content review.
- Strong understanding of core mathematics topics such as algebra, geometry, trigonometry, calculus, linear algebra, discrete mathematics, probability, statistics, number theory, combinatorics, differential equations, and mathematical proofs.
- Ability to evaluate math content against detailed rubrics and identify issues such as incorrect assumptions, flawed reasoning, invalid proofs, calculation errors, notation problems, missing steps, hallucinated facts, or incomplete explanations.
- Comfortable reviewing both conceptual explanations and step by step solutions, including whether each step logically follows from the previous one.
- Familiarity with mathematical tools or workflows such as LaTeX, Python, MATLAB, R, WolframAlpha/Mathematica, GeoGebra, Desmos, spreadsheet modeling, or symbolic computation tools is preferred.
- Experience leading or supporting remote teams of trainers, annotators, reviewers, educators, technical writers, or QAs is strongly preferred.
- Comfortable working in fast moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
- Highly detail oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation.
- Experience with AI training, data annotation, large language models, prompt/response evaluation, mathematical content QA, or rubric based LLM evaluation is a strong plus.
Key Responsibilities
- Quality monitoring: Spot check mathematics items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues.
- Mathematical review: Evaluate AI generated math explanations, proofs, derivations, calculations, word problem solutions, diagrams/descriptions, and step by step reasoning for correctness and clarity.
- Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and math specific review standards.
- Question handling: Respond to trainer/QA questions clearly and promptly, especially around reasoning validity, notation, assumptions, solution methods, proof structure, formatting, and rubric interpretation.
- Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow ups, and flag availability issues when needed.
- Documentation: Create and maintain mathematics project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials.
- Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and mathematics specific review requirements.
- Quality alignment: Ensure all trainers and QAs apply mathematics guidelines consistently and understand updates as projects evolve.
- Error pattern analysis: Identify recurring issues such as skipped reasoning steps, invalid simplifications, wrong formulas, notation inconsistencies, arithmetic mistakes, or answers that are correct but poorly justified.
- Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for mathematics AI training projects.
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