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Clipboard Health is a Y Combinator-backed, profitable marketplace platform connecting healthcare professionals with facilities across the U.S. Founded in 2016, the company has grown to over 1,000 employees and is the leader in long-term care staffing while expanding into home health, hospitals, and beyond.
You will build and lead Clipboard's Applied Science function from the ground up, owning the roadmap and vision for quantitative science across the marketplace. You'll manage a small team of Applied Scientists and grow the function to support the company's expansion.
The team owns the quantitative infrastructure underlying the marketplace: pricing algorithms, auction mechanisms, causal models, metric definitions, and experiment frameworks. Some work ships directly as product features; other work becomes the analytical foundation that product, engineering, and operations teams depend on company-wide.
Key responsibilities include:
- Setting the bar for the Applied Science function: defining key metrics, measurement approaches, and marketplace performance reporting
- Deciding the team's priorities and roadmap, balancing production work with analysis that enables other teams
- Determining when problems require rigorous causal identification versus directional answers, and pushing back when expected value is low
- Hiring and developing Applied Scientists across levels while remaining hands-on with important individual contributor problems
- Working directly with engineers to move models from prototype to production
- Communicating quantitative reasoning clearly to product managers, operators, and leadership
This is a player-coach role at the intersection of engineering, product, finance, and operations. You'll mentor the team while staying close enough to technical work to contribute directly. The toolkit includes causal inference, machine learning, randomized experiments, discrete-time hazard models, auction and mechanism design, and time series analysis.
REQUIREMENTS:
- Bachelor's degree in economics, statistics, engineering, mathematics, or another quantitative field, or equivalent practical experience
- Experience building and deploying quantitative models in applied or research settings
- Fluency querying data directly with SQL or equivalent tool
- Experience designing and analyzing controlled experiments
- 1–3 years of experience managing or leading a team
PREFERRED QUALIFICATIONS:
- PhD or Master's in economics, operations research, statistics, engineering, or related field, or equivalent quantitative depth from research or trading
- Track record of taking prediction models from idea to production
- Strong grounding in experimental design and causal inference
- Experience in quantitative finance, economic consulting, marketplaces, or other data-intensive environments where decisions have real business consequences
