Senior Product Designer - Dashboard & Analytics

About This Role

Tile Health’s dashboards surface critical insights on population health, quality metrics, and financial performance to healthcare executives and care teams. The Senior Product Designer for Dashboard & Analytics will own the end-to-end design of these data-dense experiences, translating complex health data into clear, actionable visualizations. You will balance information density with clarity, always designing for the time-constrained clinician or administrator.

What You'll Do

• Lead the design of analytics dashboards from concept through delivery, including information architecture, interaction design, and visual design
• Conduct user research with clinical leaders, quality managers, and health system executives to understand their analytical workflows and pain points
• Define data visualization best practices for the organization, establishing chart type guidelines and color usage conventions for health metrics
• Prototype interactive data exploration flows and validate with users through moderated usability testing
• Collaborate with data engineers and product managers to ensure dashboard designs are feasible given available data granularity and freshness

What We're Looking For

• 5+ years of product design experience with at least 2 years focused on data visualization or analytics products
• Strong portfolio demonstrating expertise in dashboard design, information hierarchy, and complex data presentation
• Proficiency in Figma with experience creating interactive prototypes for data-rich interfaces
• Understanding of data visualization principles (Tufte, Few, Munzner) and ability to apply them in practical product contexts
• Experience conducting both qualitative and quantitative user research
• Excellent communication and storytelling skills for presenting design rationale to stakeholders

Nice to Have

• Experience designing analytics products for healthcare audiences
• Familiarity with charting libraries such as D3.js, Recharts, or Vega-Lite
• Understanding of statistical concepts sufficient to design for confidence intervals, trend lines, and cohort comparisons