Marketplace Data Science Lead & Decision Optimization

DAT Freight & Analytics; Seattle (WA); Hybrid; USD 140,000 - 220,000; Full time

Benefits offered by this job

Hybrid work environment

Job summary

DAT Freight & Analytics is seeking an Applied Science Manager to lead the Marketplace & Decision Optimization team. You will guide a group of applied scientists, own models and experiments, and shape how data-driven insights influence pricing, engagement, and product strategy at scale.

You will combine leadership with hands-on technical work, setting high standards for experimentation, causal inference, and collaboration with product and engineering teams across the marketplace and subscription

Qualifications

• PhD or MS in a quantitative field with 6+ years of industry experience in applied/data science, including 2+ years managing scientists
• Strong SQL and Python, able to review model and experiment designs
• Experience with two-sided marketplaces, auctions, pricing, or recommender systems
• Ability to communicate complex statistical concepts to leaders

Responsibilities

• Lead and grow a team of applied scientists; set the technical roadmap, hire, and grow talent
• Hands-on work: own models, experiments, and analyses on high-leverage problems
• Bring experimentation and causal inference to decisions across marketplace and subscription businesses
• Raise the experimentation bar across DAT; collaborate with product and engineering to improve rollouts and tests
• Partner with product, engineering, design, finance, and go-to-market to translate evidence into decisions

Skills

SQL proficiency

Python proficiency

Causal inference

Experiment design

Leadership of scientists

Communication

Education

PhD in Statistics, Economics, Econometrics, CS, or Applied Mathematics

MS in Statistics, Economics, Econometrics, CS, or Applied Mathematics

Job description

DAT Freight & Analytics is seeking an Applied Science Manager to lead the Marketplace & Decision Optimization team. You will guide a group of applied scientists, own models and experiments, and shape how data-driven insights influence pricing, engagement, and product strategy at scale.

You will combine leadership with hands-on technical work, setting high standards for experimentation, causal inference, and collaboration with product and engineering teams across the marketplace and subscription