Data Analyst, Commercial Analytics - Virta Health

Virta Health is on a mission to reverse metabolic disease in one billion people. Current treatment approaches aren’t working—over half of US adults have either type 2 diabetes or prediabetes, and obesity rates are at an all-time high. Virta is changing this by helping people reverse their metabolic condition through innovations in technology, personalized nutrition, and virtual care delivery reinvented from the ground up.

This role sits on Virta’s Commercial Analytics team and will focus on the analytics that help Virta measure and communicate value to clients. You will partner closely with Client Success, Commercial, Finance, Product, and Analytics teams to ensure Virta’s value is measured accurately, communicated clearly, and used to strengthen client relationships and inform strategy. This is a hands-on role centered on executing recurring measurement and reporting workflows while improving the underlying systems that support Virta’s growing client base.

Responsibilities

• Deliver Commercial Analytics: Execute recurring and ad hoc analyses across client reporting, performance guarantees, dashboards, and other commercial priorities.
• Measure Client Value: Develop a strong understanding of Virta’s value model and apply its measurement frameworks to accurately calculate, validate, and communicate client outcomes.
• Turn Data Into Strategy: Build dashboards and analyses that surface trends, answer business questions, and inform client and commercial decision-making.
• Partner With Stakeholders: Work directly with Client Success and cross-functional partners to translate complex questions into clear analytical approaches, insights, and client-ready narratives.
• Build for Scale: Strengthen metric definitions, documentation, data quality, and repeatable workflows while using automation and AI to improve speed and reliability.

90-Day Plan

First 30 Days

• Develop a strong understanding of Virta’s commercial model, client value frameworks, products, and core analytics workflows.
• Review existing client reports, dashboards, performance-guarantee calculations, and metric definitions.
• Build relationships across Analytics, Client Success, and Product.
• Begin supporting recurring reporting cycles while learning systems and expectations.

Days 31–60

• Begin owning one recurring commercial analytics workflow, ensuring deliverables are accurate, timely, and clearly communicated.
• Support client-specific analyses and begin participating in stakeholder and client-facing conversations.
• Identify opportunities to improve dashboards, documentation, data quality, or workflow efficiency.

Days 61–90

• Independently manage multiple commercial analytics workflows from question definition through final delivery.
• Deliver an improvement that increases the scalability, reliability, or usefulness of an existing analysis or reporting process.
• Use analytical findings to provide a clear recommendation or insight that supports a Product or Commercial decision.

Must-Haves

• 3–5 years of experience in a business analyst, analytics, or data-focused role.
• Strong SQL skills to explore data, validate metrics, and support rigorous, audit-ready outputs.
• Ability to define metrics clearly and ensure consistency through documentation and governance.
• Systems-oriented mindset with a track record of improving or automating repeatable processes.
• Strong communication skills, with experience translating complex data into clear insights for internal and external audiences.

Nice-to-Haves

• Experience building dashboards in BI tools (e.g., Looker or similar).
• Experience supporting client-facing analytics or value reporting.
• Familiarity with modern data stack tools (e.g., dbt, data modeling concepts, version-controlled analytics workflows).

Company Culture

• People First: Take care of yourself, your peers, and patients equally.
• Ownership: Take initiative while empowering others to do the same.
• Impact: Prioritize positive impact over busy work.
• No Ego: Everyone has something to bring to the table regardless of experience.
• Transparency: Promote trust and empowerment through open access of information.
• Evidence-Based: Prioritize data and science over seniority or dogma.
• Iterative: Take risks and rapidly iterate.