Job Description
📋 Description Design and build knowledge tracing and longitudinal learner models to surface mastery features Define operational mastery and progression constructs, targets, and evaluation criteria Build robust training and scoring for noisy, incomplete, evolving learner data Own model trustworthiness: validity, calibration, fairness, stability, interpretability Partner with engineering to productionize learner models into reliable services Collaborate with product and learning partners to translate theory into scalable product systems 🎯 Requirements 6+ years in applied ML/data science with models shipped to products Deep expertise in knowledge tracing, sequence/temporal modeling, Bayesian approaches, or psychometrics Working understanding of computational psychometrics and construct measurement Ability to evaluate models beyond accuracy: calibration, uncertainty, fairness, robustness, interpretability Experience with longitudinal data and models that stay stable and interpretable over time Strong Python and ML stack skills; develop and iterate on modeling pipelines; Onsite Tue/Wed collaboration required 🎁 Benefits Competitive compensation plus ownership program Flexible remote, hybrid, and in-office culture Generous time off and the Dim the Lights period Wellness programs and mental health support Learning and development resources with tuition reimbursement The technology and tools you need to do your best work
