Principal Data Scientist, Pricing

TL;DR

Principal Data Scientist, Pricing (ML): Building and iterating on machine learning systems that power real-time freight pricing recommendations with an accent on dynamic spot/contract pricing, lane-level demand forecasting, and price elasticity. Focus on designing pricing experiments, validating model performance, and partnering with engineering to deploy, monitor, and govern production models in an ambiguous, early-stage environment.

Location: Los Angeles, CA; Remote

Company

hirify.global partners with a major North American freight and logistics company to reinvent how the trucking industry prices, bids, and captures value.

What you will do

• Own the data science function for freight pricing and revenue optimization.
• Build and iterate on ML models for dynamic spot/contract pricing, lane-level demand forecasting, load acceptance optimization, price elasticity, and market benchmarking.
• Design and run pricing experiments to validate model performance and generate actionable insights for product and commercial decisions.
• Partner with engineers to move models from prototype to production, including deployment guidance, monitoring, and model maintenance.
• Validate early business assumptions about freight pricing mechanics and support monetization strategy with data-driven analysis.
• Set data science best practices and model governance standards for the venture.

Requirements

• 8+ years of experience in data science and machine learning, with meaningful experience in pricing, revenue optimization, or demand modeling.
• Proven experience building and deploying ML models in production for dynamic pricing, price elasticity, willingness-to-pay, bid optimization, or similar.
• Strong quantitative modeling background (data science, operations research, or systems engineering).
• Experience applying these methods to pricing, network optimization, supply/demand balancing, or marketplace dynamics in production environments.
• Comfort working in ambiguous, early-stage environments where the roadmap and data quality are evolving.
• Proficiency with Python and SQL, plus relevant ML libraries.

Nice to have

• Freight/logistics (or adjacent) experience such as rideshare, airlines, ecommerce fulfillment, or digital marketplaces.
• Experience with A/B testing frameworks for pricing experiments.
• Experience applying reinforcement learning to dynamic pricing or sequential decision problems.
• Exposure to network optimization or capacity planning in logistics.
• Experience with cloud data infrastructure (AWS, GCP, or Azure) and warehouse tooling (Snowflake, Databricks, dbt).

Culture & Benefits

• Remote work option while supporting a venture focused on production-grade ML for pricing.
• High ownership of modeling, experimentation, and model governance for the pricing product.
• Close collaboration with product and engineering to translate model outputs into decisions.
• Opportunity to work with deep freight data and tackle long-standing pricing challenges in trucking.