Senior Product Analyst, Growth

Midi Health•Palo Alto, CA

21h•$150,000 - $175,000•Hybrid

About The Position

Midi Health is the fastest-growing virtual clinic focused exclusively on women’s midlife health. We deliver insurance-covered care for women navigating perimenopause, menopause, and other hormone-related health challenges. Our care model combines clinical expertise with technology to improve access, outcomes, and quality of life for millions of women. We’ve raised backing from top-tier investors and are scaling rapidly, now caring for hundreds of thousands of patients across the U.S. If you’re energized by building in a fast-growth, mission-driven environment, we’d love to meet you! About the Role We are looking for a Senior Product Analyst to partner with our Product, Engineering, and Design teams. You will be the data-driven voice in the room, ensuring that every feature we build is grounded in evidence and every experiment we run yields actionable learning. In this role, you will own the feedback loop between our users and our product roadmap. You won’t just measure what happened; you will uncover why it happened and help define what we should build next for growth and retention opportunities. You will champion a culture of experimentation and rigorous impact measurement.

Requirements

Advanced ability to query large datasets and manipulate complex event streams.
Experience with data modeling and dbt to transform raw event data into clean, analysis-ready models.
Deep expertise in event-based analytics platforms (Amplitude, Mixpanel, etc.).
Strong grasp of statistics required for experimentation (hypothesis testing, p-values, confidence intervals, power analysis).
Experience going beyond correlation to establish causality using quasi-experimental designs (e.g., Difference-in-Differences, Regression Discontinuity, or Propensity Score Matching) when standard A/B testing is not feasible.
Proficiency in BI tools (e.g., Tableau, Looker, or Sigma) to build automated, self-serve dashboards for stakeholders.
Proficiency in a scripting language for advanced statistical analysis or data manipulation is preferred.
You can translate data points into a narrative about human behavior.
You understand attribution modeling and incrementality testing to measure the true impact of growth initiatives.
Partner with Lifecycle/Marketing teams to optimize patient re-engagement via email, SMS, etc.
You know the difference between a vanity metric and a metric that drives business value, and have experience in defining and measuring 'meaningful' retention (e.g., clinical adherence or long-term health outcomes) rather than just session frequency.
You are the guardian of statistical accuracy, ensuring we don't make decisions based on noise.
4-6 years in Product Analytics or Data Science.
Experience working with Product Managers and Engineers on growth/retention initiatives.
Experience designing and analyzing A/B tests at scale.
Candidates must be authorized to work in the U.S. without current or future sponsorship needs.

Nice To Haves

Experience in high-growth startups, marketplaces, or healthcare operations is highly preferred.
Good understanding of HIPAA compliance and data privacy best practices when handling Protected Health Information (PHI).

Responsibilities

Use data to reconstruct the user (patient) experience, identifying friction points in conversion funnels and "aha!" moments for retention.
Perform exploratory analysis to understand user segmentation, feature usage patterns, and retention drivers.
Evaluate funnel step conversion and their impact on patient growth and retention, and collaborate with the product team on feature requirements and prioritization based on these findings.
Partner with Product Managers during the ideation phase to estimate the potential impact of roadmap initiatives using historical data.
Own the experimentation framework. You will design test plans, calculate sample sizes, define success metrics, and analyze results for statistical significance.
Define and track success metrics for new features, conducting post-mortem analyses to iterate on product strategy.
Maintain data integrity by defining tracking plans (events/properties) and working with engineering to ensure analytics are implemented correctly.
Embed directly within the product and eng org to help prioritize the roadmap based on quantitative evidence.
Democratize data access by training PMs and Designers on how to use product analytics tools.