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DAT Freight & Analytics

On-demand freight marketplace with analytics

Applied Science Manager - Marketplace

Data ScienceUpdated on Nov 9
Full-timeSeattle, WA, USA

About the Job

Requirements

  • A PhD or MS in Statistics, Economics, Econometrics, Computer Science, Operations Research, Applied Mathematics, or a related quantitative field.
  • At least 6 years of industry experience in applied science or data science, or at least 4 years with a PhD, including at least 2 years directly managing scientists.
  • A strong foundation in experimental design and causal inference, including power analysis, variance reduction, sequential testing, and quasi-experimental methods.
  • Strong SQL and Python proficiency, technical depth to review model and experiment designs and challenge assumptions, a record of rigorous decision-shaping analysis, and fluency in AI-assisted development with the judgment to verify AI-generated work.
  • Experience with two-sided marketplaces, auctions, pricing, or recommendation systems where multi-agent interactions shape outcomes.
  • A track record of hiring, developing, and retaining scientists, setting technical direction, and managing performance.
  • Demonstrated ability to change how a cross-functional organization makes decisions and explain nuanced statistical tradeoffs to senior technical and non-technical leaders.

Responsibilities

  • Lead, hire, and grow a team of applied scientists, set the technical bar and roadmap, and remain hands-on with models, experiments, and analyses on high-leverage problems.
  • Bring experimentation and causal inference to decisions across the transactional marketplace and subscription business.
  • Raise experimentation standards across product and engineering teams by improving rollout and test design and decision-making based on collected data.
  • Manage and grow the Marketplace & Decision Optimization team, set its technical roadmap, prioritize work by business impact, and hire scientists as the remit expands.
  • Advance carrier engagement recommendation systems, auction design, and automated negotiation models to improve liquidity, match quality, and economic outcomes for brokers and carriers.
  • Build science capabilities for subscription monetization and growth, including price elasticity, willingness to pay, tier adoption, upgrade paths, upsell, and cross-sell decisions.
  • Design and analyze experiments in a two-sided marketplace using switchback, cluster-randomized, and quasi-experimental designs where randomization is constrained, and quantify heterogeneous and long-term effects.
  • Define reusable standards for experiment design, power analysis, guardrail metrics, and readouts, and partner with the ML and Experimentation Platform team to make them standard across teams.
  • Partner with product, engineering, design, finance, and go-to-market leaders to turn evidence into decisions about what DAT builds, prices, packages, and launches.
  • Frame problems precisely, specify work clearly for AI tools, review modeling choices, and take on difficult technical problems when needed.
  • Set standards for experiment design, metrics, and readouts, and advocate for them with product, engineering, and design leaders.
  • Partner with product leaders to frame decisions, define success, and identify opportunities for science to inform decisions.
  • Build trust across product, engineering, and design teams, communicate with technical and non-technical audiences, and push back constructively.

Desired Qualifications

  • Experience raising experimentation standards at an organization, including building standards, review processes, or an experimentation culture.
  • Experience applying bandits, reinforcement learning, or adaptive experimentation in production.
  • Experience with subscription or SaaS monetization, including pricing, packaging, willingness to pay, or upgrade and retention modeling.
  • Experience redesigning how a science team works around AI tools and demonstrating changes in speed and quality.
  • Experience in freight, logistics, or transportation technology.

About the Company

DAT Freight & Analytics

On-demand freight marketplace with analytics

DAT Freight & Analytics runs the DAT Network, North America’s largest on-demand freight marketplace, linking shippers who need to move goods with carriers who transport them and brokers who facilitate transactions. Its core offering is a subscription-based platform that includes a robust load board and analytics tools, with DAT iQ providing market intelligence to help plan and optimize freight operations. The company differentiates itself by the size of its network, its long history dating back to 1978, and its focus on data-driven optimization and automation. Its goal is to make freight matching more reliable and efficient by improving visibility, reducing uncertainty, and speeding up the transportation process for brokers, carriers, and shippers.

Company size
501-1,000
Company stage
Acquired
Total funding
Not listed
Headquarters
Beaverton, OR
Founded
1978

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