Senior Data Scientist

Role Overview

Join Coursera as a Senior Data Scientist to drive product and business strategy through measurement, experimentation, and causal inference. You’ll partner with product managers, engineers, and learning designers to improve the learning experience for millions of learners.

Responsibilities

• Design, execute, and analyze A/B and multivariate experiments to evaluate product changes, learning interventions, and personalization strategies.
• Build statistical and machine learning models to support product roadmap decisions, learner segmentation, and personalization at scale.
• Apply psychometric methods to measure learning outcomes and assessment quality; help define and operationalize educational constructs with curriculum and learning design teams.
• Translate complex statistical results into clear narratives for non-technical audiences and senior leadership.
• Use causal inference and advanced experimentation techniques (e.g., power analysis, sequential testing) and handle assumption violations.

Requirements

• 7+ years applying data science to product or business problems and influencing decisions with rigorous analysis.
• Strong data visualization and communication skills for cross-functional stakeholders.
• Proven experience designing and analyzing controlled experiments (A/B tests) at scale, including:
  • Power analysis
  • Sequential testing
  • Managing violations of standard assumptions
• Expert applied statistics knowledge: statistical inference, hypothesis testing, causal inference, Bayesian methods, and experimental design.
• SQL and advanced Python proficiency, including:
  • Pandas, NumPy
  • SciPy, Statsmodels, scikit-learn
• Graduate-level background in psychometrics/educational measurement, such as:
  • IRT (Item Response Theory)
  • Latent trait models
• Experience with ML in production: feature engineering, validation, bias-variance trade-offs, and monitoring.
• Experience with causal inference beyond A/B testing (e.g., synthetic control, propensity score matching, uplift modeling).
• Familiarity with learning analytics for knowledge acquisition, skill development, and learner progression.
• Background/experience in educational technology and large-scale online learning environments.
• Exposure to survival analysis, time-series forecasting, or longitudinal modeling.
• Experience with Airflow, Databricks, and/or Looker for orchestration and self-serve analytics.

Nice to Have

• Experience with Amplitude (or similar product analytics platforms).
• Graduate study/research in educational measurement or psychometric modeling.

Location / Work Style

• Full remote (listed with Ottawa, CA).