Healthcare Data Analyst

Mindoula is looking for a Data Analyst with a passion for visualizing and digging into trends in healthcare claims and operational datasets. You’ll work on datasets that enable Mindoula to better serve and engage members and also deliver public health services in smarter, more efficient ways. In this position, you will have the agency to own problems from start to finish and work directly with business stakeholders who act on the insights you discover. This role has regular external deadlines so you’ll need to be a dependable timely source of insights.

Location... This is a 100% remote position that must be located in the United States. Mindoula is not able to provide any type of employment sponsorship at this time.

What You'll Do...

• Create and present clear and actionable data visualizations and reports to communicate findings and insights to stakeholders.
• Extend our business intelligence functionality to maximize self-service and automate requests.
• Design and execute complex SQL queries and scripts to extract, transform, and analyze data from various sources, ensuring data accuracy and integrity.
• Perform exploratory data analysis to uncover trends, patterns, and insights that contribute to business and clinical objectives.
• Provide expert-level data validation to ensure data quality and consistency, identifying anomalies and inconsistencies in data sets.
• Collaborate closely with cross-functional teams to understand and define data requirements for adhoc queries and data validation requests.
• Develop and maintain documentation for query and data validation processes, ensuring knowledge sharing and best practices across the team.
  
  

What You'll Need...

• Bachelor's in a relevant field such as Statistics, Mathematics, Computer Science, or a related quantitative discipline.
• Proven experience (3+ years) as a Data Analyst in the healthcare space.
• Proficiency in SQL and at least one business intelligence tool experience with relational databases (e.g., MySQL, PostgreSQL).
• Proficiency in data visualization tools such as Tableau, Power BI, Looker, SuperSet, or a similar tool.
• Familiarity with scripting languages (e.g., Python, R) for data manipulation and analysis is required.
• Strong analytical and problem-solving skills, with the ability to translate complex data into meaningful insights.
• Experience with data validation techniques and best practices to ensure data accuracy and integrity.
• Excellent communication skills, with the ability to present findings and insights to both technical and non-technical stakeholders.
• Detail-oriented mindset with the ability to manage multiple adhoc requests simultaneously.