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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 concepts clearly and concisely.

  • Experience in specifying cloud architecture using Terraform is a plus.

  • Familiarity with AWS cloud architectures.

  • Healthcare or insurance experience, and/or experience working in a startup is preferred.

  • Thoughtful collaborator with a passion for building analytical systems while balancing the tradeoffs between speed and thoroughness in development and scalability.

Our Values

We are an Equal Opportunity Employer and our employees are people with different strengths, experiences and backgrounds, who share a passion for improving people's lives. Our definition of diversity not only includes race and gender identity, but also age, disability status, veteran status, sexual orientation, religion and many other parts of one’s identity. We believe all of our colleague’s points of view are integral to our success, and that inclusion is everyone's responsibility and a cause of beautiful things. 

We welcome candidates from all backgrounds and are committed to a fair hiring process free from discrimination and focused around problem solving, improvement, and mutual empowerment.

Compensation and Benefits

The salary range Pearl Health expects to pay for this position is between $160,000-$180,000 per year.  Full time employees are also eligible for annual discretionary bonus. Where a given candidate falls within that range will depend on a variety of factors, including, but not limited to, the candidate’s relevant skills, experience and location, labor market conditions and participation, if any, in other compensation arrangements.  Pearl Health provides its employees a competitive benefit package - for more information please review our benefits page.

Agency Submissions

We are not currently working with contingency search firms. If a resume is submitted to any Pearl Health employee by a third party without a valid written and signed search agreement, it will become the property of Pearl Health and no fee will be paid, irrespective of whether the candidate is hired.

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What You Should Know About Staff Data Analyst, Pearl Health

At Pearl Health, we're redefining the future of healthcare, and we're looking for a passionate Staff Data Analyst to join our team in Boston! In this pivotal role, you'll use your analytical prowess to build a robust data analytics infrastructure that will drive data-informed decisions impacting our clinical outcomes and financial health. You will tackle fascinating challenges related to practice engagement and patient spend insights by collaborating closely with our talented Data Science, Product, Engineering, and Customer Success teams. Your role will include designing and maintaining data pipelines using Snowflake and dbt, ensuring that we maintain high data quality standards as you help translate the company’s goals into actionable strategies. With your expertise in data architecture and high-level communication skills, you will mentor fellow data analysts and play a key role in establishing best-in-class data practices. Your work will help convert raw data into insights for general stakeholders while evaluating new technologies to ensure we keep pace in this ever-evolving industry. At Pearl, your contribution will make a real difference as we empower primary care providers and improve patient care on a national scale. If you’re looking to utilize your unique skills in a role where you can truly impact the healthcare experience, we’d love for you to consider this opportunity!

Frequently Asked Questions (FAQs) for Staff Data Analyst Role at Pearl Health
What are the primary responsibilities of a Staff Data Analyst at Pearl Health?

As a Staff Data Analyst at Pearl Health, your main responsibilities will include building and maintaining data pipelines, designing data architectures, and developing analytical models that provide insights for our operational strategies. You'll collaborate across multiple teams to translate data into actionable insights and also mentor junior analysts in best practices.

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What qualifications are required for the Staff Data Analyst position at Pearl Health?

To be considered for the Staff Data Analyst role at Pearl Health, a Bachelor's or Master's degree in a quantitative field such as Statistics, Mathematics, or Computer Science is essential. Additionally, you should have over 8 years of experience in business analytics, with a strong focus on data pipeline development and proficiency in SQL and Python.

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How does Pearl Health support the growth of its Staff Data Analysts?

Pearl Health is committed to not only enhancing patient care through data but also to fostering the professional growth of its Staff Data Analysts. The role includes opportunities for mentorship, working on high-impact projects, and gaining exposure to cutting-edge data technologies, which aligns with our goal to empower analysts in their careers.

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What tools and technologies should a Staff Data Analyst at Pearl Health be familiar with?

A Staff Data Analyst at Pearl Health should be well-versed in using tools such as Snowflake, dbt, and Python for data manipulation and analysis. Familiarity with cloud computing architectures, particularly AWS and Terraform, will also be advantageous in this role.

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What is the salary range for the Staff Data Analyst position at Pearl Health?

The expected salary range for the Staff Data Analyst position at Pearl Health is between $160,000 and $180,000 per year. This range can vary based on relevant skills, experience, and location, alongside participation in compensation arrangements.

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Common Interview Questions for Staff Data Analyst
Can you explain your experience with building data pipelines?

In your response, detail your hands-on experience with building data pipelines, specifically mentioning technologies like Snowflake and dbt. Discuss a specific project where you successfully implemented a data pipeline, focusing on challenges you faced and how you overcame them.

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How do you ensure data quality and accuracy in your analyses?

Talk about the measures you implement to ensure data quality, including validation processes and checks. Mention any specific frameworks or tools you use to maintain high standards and provide an example of how this impacted a previous project.

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Describe a time you had to collaborate with cross-functional teams?

Share an example of a successful collaboration with teams such as Data Science, Product, or Engineering. Highlight how you navigated differing opinions or challenges and how the collaboration led to impactful results.

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What are some best practices in data architecture you follow?

Discuss your philosophy on data architecture, including schema design and optimization strategies. You can reference best practices like normalization, governance, and data ontologies that enhance dataset utility.

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How do you handle ambiguity in your projects?

In your answer, describe techniques you use to clarify requirements when working in ambiguous scenarios. Explain how you ask the right questions and gather necessary information from stakeholders to define project scopes.

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What techniques do you use for data visualization?

Explain your preferred data visualization tools and techniques. Discuss how you determine the most effective ways to present data to various stakeholders and provide an example of a visualization that significantly influenced a decision.

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How do you prioritize tasks in a data analytics project?

Describe your approach for prioritizing tasks, including how you assess project impacts, deadlines, and resource availability. Provide an example of a project where you had to manage multiple tasks effectively.

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What experience do you have with SQL and Python?

Talk about your proficiency in SQL and Python, providing specific examples of how you’ve utilized these languages for data manipulation and analysis in previous roles. Highlight any complex queries or data models you've created.

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How do you stay current with new data technologies?

Discuss your methods for keeping up to date with advancements in data technology, such as attending industry conferences, participating in online forums, or engaging with professional networks. Mention any recent tools or technologies you’re excited to learn more about.

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What motivates you to work in data analytics, especially in healthcare?

Share your passion for data analytics and its impact on healthcare. You might mention your interest in making a difference in patient care, improving clinical outcomes, or how your personal values align with the mission of Pearl Health.

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EMPLOYMENT TYPE
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DATE POSTED
April 2, 2025

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