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Popular mid-level Data Scientist role with broad production ML requirements increases applicant competition.
Core ML and data skills transfer across industries, but education and government domain experience is beneficial.
No explicit years but requires strong ML, deployment, and statistics skills, creating moderate filtering.
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Develop predictive machine learning models to improve learner outcomes like dropout risk and knowledge gaps.
Design and analyze A/B experiments and perform causal inference to guide product and curriculum decisions.
Deploy and monitor ML solutions end-to-end, including building dashboards and communicating findings to non-technical stakeholders.
Strong knowledge of Machine Learning, Statistics, and Data Analysis.
Proficiency in Python, SQL, and related data science libraries.
Experience working with large datasets and data visualization tools.
Work Experience Required: Not explicitly mentioned in the JD.
Comfortable operating in a high-ambiguity, early-stage setup environment with strong ownership and rapid iteration.
Experienced in end-to-end ML solution deployment including feature store design and pipeline automation.
Able to bridge technical analyses to non-technical stakeholders, especially in education or public system domains.