Assessment Designer & Learning Analyst

Mercors mission is to organize human intelligence to power the AI economy. Were a leading AI data company building the layer between human expertise and frontier models. Millions of domain experts on the platform are paid over $4 million per day to train frontier AI models. Mercors APEX benchmark family measures AIs real-world impact on professional work. Mercor Enterprise brings this same infrastructure to Fortune 500 companies: helping companies capture how their best people actually work translating that expertise directly back into agents.

Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious fast-paced and deeply committed team. Youll work alongside researchers operators and AI companies at the forefront of shaping the systems that are redefining society. Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco NYC or London offices.

Were looking for an Assessment Designer & Learning Analyst who can build rigorous measurement systems and use data to understand what actually drives expert performance.

This is not an instructional design role. You wont be building courses or writing training materials. You will be designing the assessments and certification frameworks that measure whether our talent experts and internal teams are genuinely skilled and then doing the analytical work to understand what those assessments reveal what predicts expert effectiveness and how our programs should evolve based on evidence. You will be working closely with the Learning & Development team to understand the relationship between materials and assessments and making recommendations to the team based on your analysis.

If youve come from an ed school background taught in a high-accountability environment and completed quantitative projects or theses and are energized by the measurement and data side of education this role is for you.

Assessment Design

• Design and continuously improve assessments and certification frameworks that validly and reliably measure expert readiness for specific project types

• Build assessments and measurements of skills that are consistent interpretable and actually predictive of on-the-job performance not just checklists.

• Develop item banks scoring guides and inter-rater reliability protocols for evaluating complex human judgment tasks.

• Run validity studies: do our assessments measure what we think they measure

Learning Analytics & Impact Analysis

• Analyze the relationship between instructional materials assessments and expert performance identifying whats working and what isnt and make recommendations accordingly.

• Analyze assessment data at the item level difficulty discrimination reliability and iterate based on findings.

• Investigate the relationship between assessment performance and real-world expert effectiveness: who performs well on our assessments and does that predict quality outcomes

• Build reports and dashboards that surface actionable insights to program and operations teams.

• Design and analyze quasi-experimental quantitative and qualitative (mixed methods) studies to understand what interventions actually move the needle on expert quality.

Ongoing Measurement & Improvement

• Track certification and assessment outcomes over time and flag when programs need revision

• Partner with learning designers and project teams to translate your findings into program improvements

• Bring a continuous improvement mindset ship measure learn iterate

Education

• Masters degree in Learning Sciences Educational Psychology Educational Measurement Psychometrics or a closely related field required

• Coursework in quantitative research methods psychometrics and educational statistics required

• Familiarity with classical test theory (CTT) and ideally item response theory (IRT)

Quantitative Skills Required This role requires genuine comfort with numbers. Were looking for someone who can do the following and show their work:

• Item-level analysis: difficulty index discrimination index inter-rater reliability (Cohens kappa Krippendorffs alpha ICC)

• Assess and report on assessment validity and reliability and know what to do when results look off

• Analyze relationships between variables: correlation regression and basic predictive modeling

• Work fluently in Excel or Google Sheets for data cleaning and summaries

• Use Python STATA or R for deeper analysis (basic proficiency expected; well grow this with you)

• Translate quantitative findings into plain-language recommendations for non-technical stakeholders

We will ask you to demonstrate this. Finalists will complete a short take-home exercise involving a real assessment dataset youll analyze item performance identify problems and recommend improvements.

Experience

• 12 years of experience in assessment design educational research learning analytics or a related role

• Teaching or similar experience in a high-accountability environment (Teach For America urban education or similar) is a strong plus; people whove lived with assessment data in the classroom understand it differently

• Experience designing assessments with a clear theory of what youre measuring not just writing questions

• A portfolio or work samples showing both assessment design and quantitative analysis we want to see how you think

Skills

• Deep understanding of measurement: validity reliability and what makes an assessment actually good

• Ability to move between data and meaning you can run the analysis and explain what it means for the program

• Strong writing you can communicate complex findings clearly to non-technical audiences

• Systems thinker you see how individual assessments connect to broader operational quality and expert performance

• Comfortable with ambiguity and rapid iteration this is a fast-moving environment and youll need to ship and improve continuously

• Experience with item response theory (IRT) or latent variable modeling

• Familiarity with data annotation labeling or AI evaluation workflows

• Experience in tech AI/ML or data operations environments

• Background in competency-based or mastery learning frameworks

• Experience building and analyzing assessments

The quality of AI systems depends on the quality of the humans who train them. Your job is to measure that quality rigorously understand what drives it and help Mercor build smarter systems for developing expert performance. Its a rare opportunity to apply serious measurement science at a company operating at the frontier of AI development where the stakes for getting it right are unusually high.

Required Experience:

IC