Senior Data Analyst

Empassion is a Management Services Organization (MSO) focused on improving the quality of care and costs on an often neglected “Advanced illness/ end of life” patient population, representing 4 percent of the Medicare population but 25 percent of its costs. The impact is driven deeper by families who are left with minimal options and decreased time with their loved ones. Empassion enables increased access to tech-enabled proactive care while delivering superior outcomes for patients, their communities, the healthcare system, families, and society. What Success Looks Like

• Collaborate with cross-functional teams to understand business requirements and report on data from various sources, ensuring data quality, consistency, and accuracy
• Calculate traditional (PMPM costs, utilization, etc.) and novel (program engagement, capitation rates, etc.) healthcare metrics from claims and product data
• Help to validate regular claims and eligibility data refreshes
• Act as a healthcare data SME on a rapidly growing Data & Analytics team
• Design, develop, and maintain algorithms and data models, using SQL and dbt
• Create visually appealing and informative visualizations and dashboards to communicate data insights and enable data-driven decision-making to stakeholders, using Looker
• Create documentation and training materials for technical and non-technical users of our data products

What You Will Bring

• 4+ years of experience in healthcare analytics, analytics engineering, or medical economics, having delivered actionable insights from big data analytics environments to Clinical, Operations, or Finance teams
• Deep familiarity with healthcare claims and eligibility data
• Strong SQL skills
• Excellent communication abilities around highly technical data topics and the ability to work with a diverse set of technical and non-technical audiences (peers, engineers, operations, external customers)
• Proficiency with BI/reporting tools (Looker, Tableau, etc.)
• Excitement about working in a fast-moving startup environment
• A bias for action and enthusiasm for fast iteration

Nice to have:

• Proficiency with dbt and templated SQL
• Familiarity with clinical healthcare data sources and standards (ADT, EHR, Labs, FHIR, USCDI, etc.)
• Experience with statistical analysis software (Python/pandas, R, etc.)

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Compensation range reflects total compensation. Empassions' philosophy is to provide competitive compensation that aligns with our mission, business, and employee needs while remaining financially responsible and applying it fairly, equitably, consistently, and transparently. We are a tech-enabled remote healthcare company. We value the impact and significance of all team functions and roles equally, regardless of where you live. We plan to update our approach, data, and practices to ensure that we align with the market at year-end 2023. This strategy ensures that our employees are paid fairly in the market for their skills, experience, and performance. We use current data to draft compensation numbers and will update the data yearly. Performance is a highly valued and meaningful driver of employee compensation within Empassion's market position. Our performance-enhanced compensation philosophy rewards employees who consistently meet and exceed performance expectations through bonus incentives at all levels. We pay through consistent and compliant practices. We have team-oriented goals and recognize performance against those goals through compensation. Everyone is an owner and is expected to add value and contribute; when Empassion wins, we all win. We are designed to be fair and equitable and conduct a pay equity audit annually to ensure fair and equitable compensation level by level, job family by job family.