Staff Data Analyst

Who we are...

Pearl Health is powering the future of healthcare. We help primary care providers and organizations to deliver quality healthcare to the patients who need it most, when they need it most — and get rewarded for keeping patients healthy.

Our technology, services, and financial tools enable better, more proactive care, decrease total cost of care across patient panels, and optimize performance in value-based care models for Traditional Medicare and Medicare Advantage.

We are a team of physicians and public health experts (Stanford, Harvard, Mount Sinai), technologists (athenahealth, Amazon, Meta, Flatiron), healthcare innovators (Centivo, Aledade, Stellar, Arcadia), and experienced risk management professionals (CVS/Aetna, Humana, Oscar) who believe that primary care providers are the key to addressing our healthcare system’s biggest challenges.

Since its founding in 2020, Pearl has expanded to partner with thousands of primary care providers in practices and organizations across 44 states. Our investors include Andreessen Horowitz, Viking Global Investors, AlleyCorp, and SV Angel.

What we hope you can do...

As a Staff Data Analyst at Pearl, you'll be instrumental in building robust data analytics infrastructure and driving data-informed decisions that impact our clinical outcomes and P&L. You will tackle challenging problems related to practice engagement, patient spend insights, network analytics, collaborating with Data Science, Product, Engineering, and Customer Success teams to identify opportunities, build robust analytical solutions, and develop and maintain KPIs that offer actionable insights to the organization. This role provides an opportunity to leverage your analytical and architectural expertise to make a tangible impact on healthcare. You'll have the opportunity to mentor other data analysts as well as have a leadership role on key projects.

What Staff Data Analyst means to us...

• Translate the company’s goals and vision into its strategy and operations by surfacing insights from quantitative analyses in business intelligence systems (Mode and Hex).

• Own the design, development, and maintenance of data pipelines in Snowflake & dbt, with a strong emphasis on data quality standards and data accuracy across various data sources, working with a high degree of autonomy in addition to support from your manager and Engineering.

• Establish and champion best-in-class data architectures, encompassing schema design, data ontologies, governance processes, and optimization strategies (query and computer fine tuning) to ensure scalable, reliable, and well-governed data assets.

• Manage ambiguity while working with cross-functional teams on complex projects, with a focus on defining data requirements, developing analytical models, and interpreting results.

• Partner with Data Engineering and Product to create end-to-end data pipelines that turn raw data into actionable insights for non-technical stakeholders.

• Contribute to the development of the data analytics roadmap and strategy by collaborating with leadership in the Data Science and Analytics organization to identify opportunities and propose technical and business-level solutions with a medium-term (1-2 year) time horizon.

• Evaluate new data technologies and tools (including data warehouses, orchestration systems, and BI tools) to enhance the team's capabilities.

• Mentor other data analysts, providing guidance on analytical techniques and best practices.

• Help your manager establish standards, design guidelines, and SOPs for analytical workflows, e.g., dashboard development, EDA, and ingestion of new datasets.

Who you are...

• Bachelor's or Master's degree in a quantitative field (e.g., Statistics, Mathematics, Computer Science, Economics, or related field).

• 8+ years of experience in delivering business analytics across the data pipeline: data ingestion, data architecture/schema design (including dimensional modeling), data transformation, data analysis, and reporting data to business stakeholders (including data visualization)

• Strong experience building end-to-end data pipelines for business stakeholders, direct experience using Snowflake, PySpark, and DBT preferred

• Demonstrated ability to design data schemas that maximize dataset utility by analyzing input data, understanding business and technical needs, and structuring staging tables, functional data marts, or conceptual data marts to capture ontological relationships.

• Expert proficiency in SQL and Python for data manipulation, analysis, and modeling.

• Excellent communication, presentation, and facilitation skills, with the ability to explain complex conc