Data Analyst

Oxbridge Health is a startup focused on episodes of care benefit plans, leveraging expertise in episode pricing and analytics to improve transparency and efficiency in healthcare. The Data Analyst will support episode pricing and analytics operations for internal stakeholders and external customers by producing analyses, reports, and visualizations that communicate data-driven insights.

• Analyze large healthcare datasets from multiple sources to support business decision-making.
• Perform exploratory data analysis and assess data quality and usability.
• Assist in developing and maintaining ETL/ELT pipelines using established templates and internal tools.
• Conduct routine data audits to identify quality issues and develop monitoring reports for pricing quality and coverage.
• Help develop workarounds for data limitations and constraints.
• Gather and document data requirements by participating in stakeholder meetings.
• Collaborate with team members to define key metrics and understand the rationale behind data requests.
• Document existing data workflows to identify inefficiencies and error-prone areas (using tools such as Miro, Confluence, and Jira).

• Bachelor's degree (ideally in a quantitative field such as statistics, mathematics, economics, or computer science).
• 1–2 years of experience using Python for data analysis, including pandas/numpy and writing robust data-processing code (handling exceptions, enforcing expected patterns, and evaluating usability/quality via EDA).
• Exposure to large-scale datasets; healthcare claims or administrative data experience is a plus but not required.
• Ability to perform descriptive analysis and translate results into clear charts and summaries.
• Strong communication skills to convert complex data into clear, actionable insights.
• Strong organizational skills and ability to manage multiple priorities in a fast-paced environment.
• Basic familiarity with Git (branching, committing, pulling, and submitting pull requests).
• Preferred: BI tools (Looker, Power BI).
• Preferred: Basic statistical concepts/models (e.g., OLS, sampling variability, conditional probability, outlier detection).
• Preferred: SQL and Python ecosystem tools (e.g., SQLAlchemy, multiprocessing).
• Preferred: Experience building reusable Python utilities, processing large datasets efficiently (e.g., chunking), and refactoring complex processes via abstraction.
• Preferred: Knowledge of healthcare markets, especially value-based care.
• Preferred: Familiarity with AI-assisted coding tools (e.g., Codex CLI, Cursor, Claude Code).

Not specified in the posting.