Applied Scientist

Clipboard•San Francisco, CA

6d•Hybrid

About The Position

Clipboard is building a new team, Applied Science, and is looking for its first outside hire. Clipboard is a Sequoia-backed marketplace connecting nurses and healthcare professionals with long-term care facilities, with over $800M in annual transactions. The Applied Science team owns the quantitative infrastructure underneath the marketplace, including pricing algorithms, auction mechanisms, causal models, metric definitions, and experiment frameworks. Some of this work ships as product, while some becomes the analytical substrate every team in the company depends on. The role involves designing systems where analytical choices are product decisions, building pricing algorithms, designing auction mechanisms, developing attendance and reliability models, and constructing experiment frameworks. The role also includes investigating key metric movements and collaborating with engineers to deploy models to production.

Requirements

Bachelor’s degree in quantitative field: economics, statistics, engineering, mathematics, etc or commensurate practical experience.
Experience building and deploying quantitative models (in applied or research settings)
Comfort querying data directly (SQL or equivalent)
Experience designing and analyzing controlled experiments

Nice To Haves

PhD in economics, econometrics, operations research, statistics, engineering, or a closely related field.
Equivalent depth from a quant research or trading environment.
Track record of building applied models, not just publishing them; you've taken something from whiteboard to production.
Sharp experimental intuition: you know the difference between a valid identification strategy and a plausible-sounding one, and you've defended that distinction in front of a skeptical audience.
Background in quant finance, economic consulting, or marketplace work is a strong signal.
Comfort collaborating with competing ideas in high-stakes data environments.

Responsibilities

Designing systems where analytical choices are product decisions
Building pricing algorithms
Designing auction mechanisms that shape how supply and demand interact
Developing attendance and reliability models that determine worker↔workplace relationships
Constructing experiment frameworks the rest of the org runs its ideas through
Investigating key metric movements when the cause isn't obvious
Taking models from prototype to production in collaboration with engineers
Writing clearly to make reasoning legible to PMs and leadership