AI-Driven Fast Math Learning Strategist $100,000 USD/year Pay is set based on global value, not the local market.
Most roles = hourly rate x 40 hrs x 50 weeks
Not accepting applications on crossover.com at this time.
Description
Fast Math is not about giving students more worksheets and hoping repetition makes them faster. Your job is to find exactly what prevents students from developing math fluency, then use AI to rebuild the learning experience until accurate calculation becomes automatic.
2 Hour Learning helps students learn core academics in a fraction of the normal school day. You will focus on our Fast Math program, using student performance data, platform data, assessment results, and student work to identify what is blocking fluency and fact mastery. The problem might be weak sequencing, the wrong practice pattern, a missing scaffold, poor feedback, or an intervention that fails to correct the underlying misconception.
This is hands-on work. You will use LLMs, AI-assisted content generation, no-code workflows, and agentic AI tools to improve practice sequences, explanations, assessments, scaffolds, and interventions. Your work succeeds when students move from effortful calculation to fast, accurate, automatic performance. If you want to use AI every day to make measurable gains in mathematical fluency, apply now.
What you will be doing
- Diagnose recurring gaps in math fluency, fact mastery, speed, and accuracy using performance data, assessments, platform data, and student work.
- Identify what is preventing automaticity, from weak sequencing and missing scaffolds to ineffective practice, feedback, assessments, or interventions.
- Use LLMs, no-code workflows, and agentic AI tools to redesign practice sequences, explanations, scaffolds, and interventions for Fast Math.
- Improve questions, answer explanations, distractors, rubrics, and assessments so they expose misconceptions and accurately measure mastery.
- Validate AI-generated or AI-modified materials for mathematical accuracy, grade fit, clarity, rigor, and alignment with Alpha's learning science standards.
What you will NOT be doing
- Producing repetitive drill exercises without evidence that they improve fluency or automaticity.
- Writing one-off lesson plans that look polished but never move mastery data.
- Stopping at analysis. You will find the learning gap, rebuild the material, and measure whether the change worked.
- Managing a traditional curriculum program, handling admin work, or coordinating a slow review process.
- Building education software products. Your focus is the math learning experience, not the app codebase.
Key responsibilities
Accelerate K-12 math fluency by continuously improving Fast Math curriculum, practice, assessments, scaffolds, and interventions until students calculate accurately and automatically.
Candidate requirements
- Bachelor's degree or higher in Mathematics, Statistics, Applied Math, Engineering, Physics, or another quantitative field.
- 3+ years of experience in math instruction, math curriculum development, assessment development, educational content creation, or learning design, especially focused on building math fluency and fact mastery and building students toward automaticity in four-function math.
- Strong K-12 math subject expertise, including accuracy, rigor, sequencing, misconceptions, fluency development, and grade-level expectations.
- Practical knowledge of learning science or instructional design, such as mastery learning, direct instruction, scaffolding, cognitive load, retrieval practice, or deliberate practice.
- Experience using AI tools to improve educational work, such as LLMs, AI-assisted content generation, no-code workflows, coding/API-based tools, or agentic AI tools.
- Ability to use student learning data to identify barriers to fluency and improve curriculum, assessments, practice, scaffolding, or interventions.
- Excellent written communication skills, especially explaining mathematical concepts clearly and precisely.
Nice to have
- Direct experience designing programs or interventions focused on arithmetic fluency, fact mastery, or automaticity.
- Experience with LLM APIs for content generation, data analysis, or adaptive learning work.
- Experience building or improving math assessments that surface misconceptions, not just procedural accuracy.
- Experience sharing education, math, or AI insights in an online community, such as Twitter/X, LinkedIn, or a public knowledge base.
Applying for a role? Here’s what to expect.
Crossover's skill assessment process combines innovative AI power with decades of human research, to take the guesswork, human bias, and pointless filters out of recruiting high-performing teams.
Chat-style screening interview.
Cognitive aptitude test.
Prove real-world job skills.
Interview with the hiring manager.
Pass proctored test.
Accept job offer.
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