Lead the data science function for a freight pricing venture: develop and deploy ML models for dynamic pricing, demand forecasting, elasticity, and load acceptance; design pricing experiments; partner with engineering to productionize and monitor models; validate business assumptions and set model governance; translate insights to product, commercial, and executive stakeholders.
About the Role
We're partnering with one of the largest freight and logistics companies in North America to reinvent how the trucking industry prices, bids, and captures value. This is a rare chance to work alongside a market leader with unmatched freight data depth, tackling pricing problems that have plagued carriers, brokers, and shippers for decades.
As the Principal Data Scientist for this venture, you'll own the modeling and analytical intelligence behind our pricing product - building, validating, and iterating on the ML systems that power how our platform recommends and adapts freight pricing in real time. You'll partner closely with product and engineering, but your core mandate is the science: the models, the experiments, the insights that make the product defensible.
What You'll Do
- Own the data science function for the venture, with freight pricing and revenue optimization as your primary domain
- Build and iterate on ML models - dynamic spot and contract pricing, lane-level demand forecasting, load acceptance optimization, price elasticity, and market benchmarking
- Design and run pricing experiments to validate model performance and surface actionable insights for product and commercial decisions
- Partner with engineers to move models from prototype into production - providing guidance on deployment, monitoring, and model maintenance
- Validate early business assumptions around freight pricing mechanics and contribute to the venture's monetization strategy with data-driven analysis
- Establish data science best practices and model governance standards for the venture
What You Bring
- 8+ years of experience in data science and machine learning, with meaningful time spent on pricing, revenue optimization, or demand modeling
- Demonstrated experience building and deploying ML models in production: dynamic pricing, price elasticity, willingness-to-pay, bid optimization, or similar
- Strong ML and quantitative modeling background - whether grounded in data science, operations research, or systems engineering
- Experience applying these skills to pricing, network optimization, supply/demand balancing, or marketplace dynamics in production environments
- Familiarity with freight, logistics, or transportation data is a strong plus - lane economics, spot vs. contract dynamics, fuel surcharges, or carrier capacity signals
- Comfort in ambiguous, early-stage environments where the data is messy, the roadmap is evolving, and you're expected to define the approach
- Experience translating model outputs and tradeoffs into clear language for product, commercial, and executive stakeholders
- Proficiency with standard data science tooling: Python, SQL, and relevant ML libraries
Nice to Have
- Experience in freight or adjacent industries with similar pricing and network complexity: rideshare, airlines, ecommerce fulfillment, or digital marketplaces.
- Familiarity with A/B testing frameworks for pricing experiments
- Experience with reinforcement learning applied to dynamic pricing or sequential decision problems
- Exposure to network optimization or capacity planning problems in logistics
- Experience working with cloud data infrastructure (AWS, GCP, or Azure) and warehouse tooling (Snowflake, Databricks, dbt)
UP.Labs Santa Monica, California, USA Office
3100 Donald Douglas Loop N, Santa Monica, CA, United States, 90405
Similar Jobs
Artificial Intelligence • Cloud • Information Technology • Security • Software • Cybersecurity • Data Privacy
Own revenue accounting, marketplace operations, month-end close, ASC 606 compliance, contract modifications, reconciliations, audit schedules, and financial reporting. Partner cross-functionally on Quote-to-Cash processes, NetSuite, Salesforce, Zone Billing, and automation initiatives. Lead system improvements, revenue recognition updates, SSP analysis, contract accounting assessments, and reporting for ARR, RPO, and disaggregated revenue metrics.
Top Skills:
ClaudeNetsuite ArmSalesforceSigmaZone Billing
Artificial Intelligence • Cloud • Information Technology • Security • Software • Cybersecurity • Data Privacy
Own the full enterprise sales and customer success cycle for large accounts, including prospecting, account planning, executive relationship management, renewals, and expansion. Collaborate with customer success, marketing, product, finance, and channel partners to close complex transactions and drive long-term growth. Maintain accurate forecasts and leverage expertise in cybersecurity, DevOps, DevSecOps, or enterprise software to sell technical solutions to Security and Engineering leaders.
Top Skills:
AICybersecurityDevOpsDevsecopsEnterprise Software
Cloud • Fintech • Food • Information Technology • Software • Hospitality
Leads Toast’s Creative Services team of 8–10 designers, developers, and content creators. Owns service delivery, capacity planning, SLAs, quality assurance, escalations, coaching, and operational excellence. Builds scalable playbooks and dashboards, partners cross-functionally with Product, Sales, Customer Success, Legal, and Finance, and improves website and custom-branded app service delivery for restaurant customers.
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
