Senior Data Analyst, Network Optimization

Brightside Health is seeking a Senior Data Analyst to support its Network product and operations teams. The role forecasts clinician capacity against patient demand, measures network performance and care quality, and partners with Product, Engineering, Network, and Clinical teams to guide decisions and experiments.

Responsibilities:

• Build and maintain the forecast model for network capacity vs. patient demand across all 50 state markets and multiple clinical care programs, and use it to guide where and when we invest in supply
• Partner with Network Ops and Clinical Talent to deliver measurement and insights that support clinician recruitment and onboarding and strengthen retention
• Develop frameworks to measure the impact of clinical quality, therapeutic alliance, and patient panel balance at both the clinician and market level
• Partner with Product and Engineering to design and run experiments on patient scheduling experiences and clinician-facing product features
• Serve as the primary analytics partner for the Network POD, explaining the drivers behind changes in performance metrics, tying them to OKRs, clinical, and financial outcomes, and presenting insights and experiment results to leadership
• Join a Data team building AI-powered analytics infrastructure that governs metric reliability and unlocks deeper analysis, including developing and documenting the data models behind KPI reporting and agentic analytics
• Solve ambiguous problems creatively with systematic, scalable solutions

Requirements:

• 8+ years of analytics experience, with a Master's degree or equivalent practical experience
• Expert-level SQL and data modeling in a cloud data warehouse (ex: BigQuery/GCP), with a track record of writing clean, performant, well-documented code
• Hands-on experience developing and scaling a dbt project, including testing, documentation, and governed metric definitions
• Strong forecasting and econometric modeling skills, ideally paired with operations research methods (capacity planning, supply-demand optimization)
• Experience designing, running, and interpreting A/B tests and other experiments, including knowing when a clean experiment isn't possible and what to do instead
• Proficiency with data visualization tools (ex: Tableau) to build dashboards and tell clear stories with data
• Fluency with AI tools and MCPs, and a habit of using them to accelerate everything from data exploration to insight generation
• Ability to turn complex analyses into clear business recommendations, with excellent written and verbal communication for audiences ranging from engineers to executives
• A self-starter mindset: you're comfortable with ambiguity, set your own priorities, and thrive in a fast-moving startup environment
• Experience in the healthcare industry
• Experience in an interdisciplinary/cross-functional field
• Startup experience