Design, build, and deploy predictive models that improve learner outcomes and product performance, including user behavior prediction, recommendations, ranking, and classification
Develop, own, and continuously improve end-to-end data science workflows, including ongoing model iteration, retraining, and performance monitoring over time
Take ownership of existing and new predictive models, diagnosing performance issues, adapting to data or product changes, and iterating to improve real-world impact over time
Partner closely with product, engineering, research, and leadership to translate ambiguous questions into data science solutions
Work closely with engineering partners to ship, maintain, and iterate on models in production; you will not be expected to build production infrastructure alone
Contribute to AI and model evaluation frameworks, including offline metrics, experimentation, and qualitative analysis
Analyze large, complex datasets to identify patterns, opportunities, and risks across our platforms
Communicate modeling approaches, assumptions, tradeoffs, and results clearly to technical and non-technical stakeholders
Write technical documentation, reports, and presentations that drive product and organizational decisions
Support responsible, ethical, and equitable use of data and AI in education-focused products

Requirements

3+ years of experience in data science, machine learning, or a closely related applied role
Experience independently developing, evaluating, and deploying data science or machine learning models in real-world settings
Experience iterating on models after initial deployment, including responding to performance drift, changing data, or evolving product needs
Strong proficiency in Python for data analysis and modeling (e.g., pandas, numpy, scikit-learn, PyTorch, TensorFlow, or similar)
Experience working with SQL and production datasets
Familiarity with model evaluation, validation, and monitoring over time
Experience with data cleaning, feature engineering, and exploratory analysis at scale
Comfort collaborating with engineers to productionize models (e.g., APIs, batch jobs, pipelines)
Clear written and verbal communication skills
Strong organizational, reliability, and collaboration skills that make you a great teammate

Benefits

401K matching
$1,500 Professional Development budget
Very generous vacation policy

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

data sciencemachine learningpredictive modelingPythonSQLmodel evaluationdata cleaningfeature engineeringexploratory analysisperformance monitoring

Soft Skills

communication skillsorganizational skillscollaboration skillsreliabilityownershipproblem-solvingadaptabilitytechnical documentationpresentation skillsstakeholder engagement