Data Analyst

Our company is a start-up that specializes in episodes of care benefit plans. We have a deep expertise in episode pricing and analytics and our goal is to bring transparency and efficiency to the healthcare market. Our company is committed to providing high-quality, affordable healthcare to our customers.

• →Analyze large amounts of healthcare data from multiple sources to support business decision making
• →Perform exploratory data analyses and evaluate data quality and usability.
• →Assist in the development and maintenance of ETL/ELT pipelines using established templates and internal tools.
• →Perform routine data audits to flag quality issues, develop reports to monitor pricing quality and coverage, and assist in developing workarounds to data limitations.
• →Assist in gathering data requirements by participating in stakeholder meetings and documenting business needs.
• →Work closely with team members to identify key metrics and understand the "why" behind data requests.
• →Document existing data workflows to help the team identify inefficiencies or error prone areas (available tools include 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 (pandas/numpy) for data analysis, including composing robust data processing code to enforce expected patterns, handle exceptions, and evaluate data usability/quality through exploratory data analyses.
• Exposure to large-scale datasets; experience with healthcare claims or administrative data is a major plus but not required.
• Ability to perform descriptive analysis and translate findings into clear charts or summaries for the team.
• Excellent communication skills, with the ability to translate complex data into clear and actionable insights.
• Strong organizational skills, with the ability to work on multiple projects and priorities in a fast-paced environment.
• Basic familiarity with Git for version control (e.g., branching, committing, pulling code, and submitting pull requests)

• Knowledge of a BI tool (i.e., Looker, PowerBI)
• Knowledge of basic statistical concepts and models (e.g. OLS, sampling variability, conditional probability, outlier detection, etc.)
• Experience using SQL databases and Python packages (pandas, sqlalchemy, multiprocessing)
• Experience developing Python utility packages for use across multiple scripts, chunking large datasets for efficient processing, and using abstraction to refactor complex processes
• Knowledge of healthcare markets, specifically with respect to value-based care
• Familiarity with AI-assisted coding tools such as Codex CLI, Cursor, Claude Code, etc.