Senior/Staff Data Scientist, Midi Health

• 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
• 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
• End-to-end ownership: You take problems from ambiguous business need through mathematical formulation, implementation, deployment, and ongoing monitoring
• Production-first mentality: You build for scale, reliability, and maintainability, not just proof-of-concept
• Pragmatic problem-solving: You balance theoretical elegance with practical constraints and can make smart tradeoffs
• Systems thinking: You understand how pieces interact and design solutions that work within broader technical and organizational systems
• 5+ years of relevant experience (Senior) or 8+ years (Staff), with demonstrated progression in scope and impact
• Proven ability to drive complex, ambiguous projects with minimal guidance
• Excellence in communicating technical concepts to non-technical stakeholders
• Track record of influencing strategic decisions through data and analytics
• Comfort working at multiple altitudes: from debugging code to advising executives

Desirable

• Reports to: Director Data Science + Analytics
• 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
• 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
• 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
• Direct impact: Your code and models will directly power critical business operations, not just inform decisions
• Full-stack data science: Equal parts algorithm design, software engineering, and strategic advisory
• Complex problem space: Work on genuinely hard technical problems with real constraints and competing objectives
• Business partnership: Regular engagement with senior leadership on high-stakes decisions
• Rapid iteration: See your work deployed and making impact quickly in a fast-moving environment
• What Success Looks Like:
• Production systems that measurably improve marketplace efficiency and patient/provider experience
• Trusted advisor relationship with demand and supply leadership
• Code contributions that meet engineering team standards for quality and maintainability
• Frameworks and tools that enable better, faster decision-making across the organization
• Visible business impact through improved utilization, reduced waste, and smarter growth investments

• Recruiter Screen- 30-45 mins
• Hiring Manager Screen- 45 mins
• Technical Screen- 1hr
• Panel Interviews- 3-4 hours + Lunch in Office in Palo Alto