Staff Data Analyst

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September 12

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Pearl Health

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Healthcare Insurance • SaaS • Finance

Pearl Health is a company dedicated to transforming primary care through value-based models. Their mission is to democratize access to value in healthcare, emphasizing quality care that rewards providers for improving patient health outcomes. Pearl Health offers data-driven insights, technology solutions, and hands-on support to primary care providers, helping them improve patient outcomes, reduce costs, and enhance their practice operations. Through strategic partnerships and their innovative Pearl Platform, they empower care providers to focus on patient care while stabilizing finances and sharing in the savings generated from quality care.

51 - 200 employees

⚕️ Healthcare Insurance

☁️ SaaS

💸 Finance

💰 $18M Series A on 2021-09

📋 Description

• Partner with Product, Engineering, Customer Success, and other teams to translate business challenges into actionable analytical solutions. • Build and maintain data assets, dashboards, and reports that deliver insights and unlock decision-making. • Collaborate with Data Engineering to design and build data marts and pipelines in Snowflake & dbt that directly serve stakeholder needs. • Translate complex business challenges into analytical frameworks, leveraging statistical modeling (e.g. regression analysis) to provide actionable recommendations and influence key decisions. • Manage a prioritized backlog of requests, balancing competing stakeholder needs with business impact. • Contribute to the company’s analytics strategy and roadmap, identifying opportunities with a 1–2 year horizon. • Mentor analysts across the team, sharing best practices in analysis, stakeholder engagement, and data storytelling. • Help establish standards and workflows for data analysis, reporting, and dashboard development.

🎯 Requirements

• 8+ years of experience delivering analytics across the data pipeline, from modeling to stakeholder engagement. • Expert-level SQL and Python skills for data manipulation, analysis, and modeling. • Proven success turning business needs into end-to-end data solutions, ideally with Snowflake and dbt. • Strong track record collaborating with non-technical stakeholders, including executives, to communicate insights clearly and persuasively. • Experience utilizing rigorous statistical methods, including regression modeling and hypothesis testing, to quantify business impact and drive key decisions. • Bachelor’s or Master’s degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics).

🏖️ Benefits

• We offer a competitive benefits package. You can learn more on our benefits page.