HealthPartners is hiring a Health Informatics Data Analyst Principal. Our mission is to provide simple and affordable healthcare. HealthPartners teams use data to improve patient and member experience, improve health, and reduce the per capita cost of health care. HealthPartners data analysts are responsible for driving adoption and use of data and analytic services and products. Data analysts work in collaborative scrum teams with developers, data scientists, and data engineers, and may share accountabilities in order to achieve sprint goals. They maintain a working knowledge of a business domain and its associated data, and provide visualization, analysis, validation, and consultation services. Together with their teams, they work on building scalable solutions to extract knowledge from data, and deliver that knowledge as needed and at scale.

ACCOUNTABILITIES:

All team members must champion and model our values of partnership, curiosity, compassion, integrity, and excellence, and must contribute to a culture of continuous learning Acts as domain experts, partnering with business groups, and data engineers to frame problems, model, clean and integrate data, and determine the best way to leverage that data in service of a goal Works with business partners to understand and create their “user stories;” they identify and clarify opportunities to leverage data analytics in service of customer or business value Independently creates, deploys, monitors, and maintains highly interactive data visualizations and analytic services Leads and participates in strategic measurement activities, including Return on Investment (ROI) analyses, Key Performance Indicator (KPI) development, risk assessment and indexing, as well as domain-specific measurements (example: readmission rates) Works with their teams to ensure data accessibility, accuracy, and quality, and may act as data stewards by contributing to management of central data stores and metadata Provides consultative, data-driven support on product and business strategy development Defines, sets up, and executes test cases to validate that analytic and software solutions meet the business acceptance criteria Communicates solution tradeoffs to business partners to frame and influence project decisions Leverages internal and external sources to validate data accuracy and benchmark results Promotes and champions our security and de-identification standards, while they handle sensitive administrative data (medical and pharmacy claims, clinical data, and other sensitive organizational data assets).

 

REQUIRED SKILLS/ QUALIFICATIONS:

Bachelor’s degree in economics, mathematics, business, computer science, data or social science, operations research, statistics, or a related quantitative field. Alternate experience and education in equivalent areas is acceptable. Experience in more than one area is strongly preferred. Five or more years direct experience using technical and analytical skills to extract, integrate, layout and interpret complex and disparate data sources (certification/other training in lieu of years of experience) Demonstrated expertise using data visualization tools such as Microsoft Power BI, Tableau, etc. Must have mastered the ability to tell stories using data Must have expertise in SQL and relational database design Expert programming skills using Python (“or similar”) Experience working with big data Demonstrated experience and skill presenting findings and actionable recommendations Must be motivated, self-driven, curious, and creative Must be skilled communicators, and demonstrate an ability to work with development teams, end users and business leaders Demonstrated ability to support and complement the work of a diverse development and / or operations team

PREFERRED QUALIFICATIONS:

Knowledge of health care operations Exposure to agile/scrum (including tools like JIRA) Experience using Azure Data Lake, DevOps, Power Automate, or other tools in the Azure Suite Working knowledge of medical terminology, medical coding systems; ICD-10, CPT4, DRG, GPI. Knowledge of statistical methods and techniques (predictive modeling, segmentation, regression, etc.) Familiarity with software development, data and integration architecture Experience working with unstructured or semi-structured data