Data Scientist

Develop and deploy predictive models to assess learner outcomes such as dropout risk, knowledge gaps, and learning pace.

Design and analyze A/B experiments to evaluate product interventions using rigorous statistical methods.

Collaborate with engineering and product teams to build automated ML pipelines, dashboards, and communicate insights to non-technical stakeholders.

Proficiency in Python, SQL, and data science libraries for model development and data analysis.

Strong knowledge of machine learning, statistics, predictive analytics, and experience with large datasets and data visualization.

Experience in designing and analyzing A/B experiments and causal inference methodologies.

Work Experience Required: Not explicitly mentioned in the JD.

Candidate thrives in ambiguous, high-ownership environments with rapid iteration and hands-on execution during early-stage vertical builds.

Experience building end-to-end ML solutions including model deployment and monitoring in production environments, preferably with cloud platforms.

Comfortable translating complex data findings into clear narratives for cross-functional teams including product and government stakeholders.