Remote Applied Science Manager for Marketplace ML

US Health Partners, LLC

Northern (KY)

Remote

USD 150,000 - 190,000

Full time

12 days ago
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Job summary

Clipboard is seeking an Applied Science Manager to build and lead the Applied Science function across the marketplace. You will own the roadmap, define key metrics, and ensure production-grade models are usable by product and engineering teams.

You’ll hire, mentor, and balance strategic projects with hands-on analysis to maximize impact. The role sits at the intersection of engineering, product, finance, and operations, with a focus on causal inference, ML, and experimental design.

Qualifications

  • Bachelor’s degree in economics, statistics, engineering, mathematics, or related field; or equivalent practical experience.
  • Experience building and deploying quantitative models.
  • Fluency querying data directly with SQL or an equivalent tool.
  • Experience designing and analyzing controlled experiments.
  • 1–3 years of experience managing or leading a team.

Responsibilities

  • Build and lead Clipboard's Applied Science function and roadmap.
  • Own metrics, measurement, and reporting for marketplace performance.
  • Lead a team of Applied Scientists; mentor across levels while contributing hands-on IC work.
  • Develop and maintain the quantitative infrastructure: pricing algorithms, auctions, causal models, experiments.

Skills

SQL
Experimental design
Team leadership
Quantitative models
Causal inference

Education

Bachelor's degree
PhD/Masters in economics or related

Tools

SQL tools

Job description

Clipboard is seeking an Applied Science Manager to build and lead the Applied Science function across the marketplace. You will own the roadmap, define key metrics, and ensure production-grade models are usable by product and engineering teams.

You’ll hire, mentor, and balance strategic projects with hands-on analysis to maximize impact. The role sits at the intersection of engineering, product, finance, and operations, with a focus on causal inference, ML, and experimental design.

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