CodePath is building the data, analytics, and AI infrastructure to power its learning platform and support tens of thousands of students nationwide. They are looking for a Data Scientist to help shape this future by supporting data pipelines, conducting exploratory analysis, building statistical and machine learning models, and developing insights that guide organizational strategy.
Requirements
- 3+ years of professional experience in data science, machine learning, analytics, or a related field
- Strong foundation in statistics, probability, and machine learning algorithms
- Proficiency with Python (pandas/polars, numpy, scikit-learn, TensorFlow or PyTorch)
- Strong SQL skills and experience working with large-scale datasets
- Experience with cloud platforms (GCP, AWS, or Azure) and deploying or maintaining data-driven applications
- Familiarity with data modeling concepts, data engineering workflows, and data pipelines
- Experience with experimental or quasi-experimental methods, causal inference, or A/B testing
Responsibilities
- Define, track, and analyze organizational impact, student outcomes, and program performance with MEL leadership
- Build and refine statistical and machine learning models for outcomes analyses, forecasting, and decision support
- Conduct deep exploratory analyses to surface trends, anomalies, and insights across large datasets
- Develop and maintain dashboards, reports, and visualizations (Tableau, streamlit, or similar) that translate complex results into clear, actionable insights
- Partner with data engineering to develop reliable datasets and features that power modeling and analytics workflows
- Support and validate data pipelines to ensure analytical datasets remain accurate, consistent, and well-structured
- Document analytical processes, models, and methodologies to ensure clarity, scaling, and reproducibility
Other
- Remote, United States
- Full-Time
- Reporting to: Lead Data Scientist
- Strong communicator able to present complex analyses clearly and accessibly
- Ability to turn ambiguous problems into structured analytical approaches
- Proactive, collaborative mindset with enthusiasm for continuous learning
