Senior​/Data Scientist

📍 Palo Alto, CA (Hybrid – 2 days/week in office)

Reports to:

Director Data Science + Analytics

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.

We're seeking an exceptional Senior to Staff-level Data Scientist to tackle one of our most critical challenges: optimizing a complex, dynamic healthcare marketplace where demand and supply must be intelligently matched across multiple dimensions. At its core, this is a sophisticated network optimization problem characterized by heterogeneous customer queues with varying booking lead times, continuous flux from cancellations and rescheduling, and multi-dimensional constraints including geography, insurance networks, provider credentials, and capacity utilization.

This role uniquely blends deep technical execution with strategic business impact. You'll write production-quality code that directly powers our platform while partnering with demand and supply leadership to shape critical decisions about where and how we grow. If you're energized by the opportunity to own complex optimization problems end-to-end—from mathematical formulation to production deployment to business strategy—this role is for you.

Technical Ownership & Execution

• Design, build, and deploy optimization and machine learning systems that power intelligent matching between patients and clinicians across a multi-dimensional constraint space
• Develop and maintain production code in our core codebase, collaborating directly with engineering teams on architecture, implementation, and deployment
• Build sophisticated forecasting models that account for lead-time dynamics, where today's demand signals translate into future supply needs weeks later
• Create optimization algorithms for resource allocation problems involving competing objectives: efficiency, quality, equity, and business constraints
• Develop monitoring and inference systems to capture demand signals, capacity constraints, and network gaps in real-time
• Build predictive models leveraging growing datasets to improve decision-making speed and accuracy in resource-constrained environments

Strategic Partnership & Business Impact

• Translate complex marketplace dynamics into actionable insights for demand and supply leaders
• Develop analytical frameworks and decision-support tools that guide hiring, capacity planning, and market expansion strategies
• Identify and quantify marketplace inefficiencies, bottlenecks, and opportunities for improvement
• Partner with cross-functional stakeholders to balance competing priorities and define success metrics

Required Technical Skills

• Advanced Python programming
  :
  You write clean, efficient, production-quality code and are comfortable working in large codebases
• SQL expertise
  :
  Complex queries, performance optimization, and data pipeline design
• Machine Learning
  :
  Hands-on experience building, deploying, and monitoring ML models in production
• Optimization
  :
  Strong foundation in mathematical optimization (linear programming, mixed-integer programming, constraint satisfaction, heuristic methods)
• Simulation & Forecasting
  :
  Experience modeling dynamic systems, time-series forecasting, and scenario analysis
• Statistical rigor
  :
  Deep understanding of experimental design, causal inference, and uncertainty quantification

Preferred Experience

• Marketplace, two-sided network, or supply chain optimization problems
• Queueing theory and stochastic processes
• Real-time decision systems and online algorithms
• Healthcare operations, insurance networks, or credentialing systems
• Large-scale batch optimization problems
• Working directly in production codebases with software…