Applied Scientist

Overview

About DAT

DAT is an award-winning employer of choice and a next-generation SaaS technology company that has been at the leading edge of innovation in transportation supply chain logistics for 45 years. We deploy a suite of software solutions to millions of customers every day, providing the most relevant data and accurate insights to help make smarter business decisions and run companies more profitably.

We operate the largest marketplace of its kind in North America, with 400 million freights posted in 2022, and a database of $150 billion of annual global shipment market transaction data. Our headquarters are in Denver, CO, and Beaverton, OR, with additional offices in Seattle, WA;
Springfield, MO; and Bangalore, India. For additional information, see

Job Final date to receive applications: 03/31/2025

DAT’s Convoy Platform team is seeking a Staff Applied Scientist to design and deploy the next generation of marketplace algorithms and intelligent decision systems that power the movement of freight across the nation.

You will tackle challenging problems in digital logistics: matching supply with demand at scale, allocating resources efficiently under uncertainty, and building systems that can make and refine complex, high-judgment decisions continuously as new information arrives.

This is a hands-on, end-to-end science role where you will:

• Conceptualize, propose, implement and iterate on algorithms that optimize a dynamic two-sided marketplace in real time
• Build decision engines that learn from feedback and guide operational and product outcomes
• Blend techniques from machine learning, optimization, and causal inference to deliver measurable marketplace improvements
• Take ideas from research to production, ensuring seamless integration into our operational systems

You will be joining at a pivotal point in DAT’s transformation, bringing together Convoy’s industry-leading technology with DAT’s scale and deep market presence to create the most advanced digital freight network in the country. The solutions you build will help move billions of dollars of freight more efficiently, reducing waste and increasing value for shippers, brokers, and carriers.

As a Staff Applied Scientist, you will set technical direction, mentor other scientists, and deliver solutions whose impact scales across teams and the broader Convoy Platform, not just within individual projects.

• Drive smarter, data-informed decision-making through advanced science features. Whether using collaborative filtering for load recommendations, leveraging a conversational AI agent powered by LLMs to deliver actionable offers to carriers, or reimagining auction mechanisms with multi-armed bandits, identify and apply the right algorithmic and data-driven approach to maximize impact. Drive innovation across the Convoy Platform to enable smarter, faster, and more reliable decisions.
• Develop feedback-aware automated decision-making systems. Build systems capable of ingesting human inputs and continuously analyze feedback from brokers and carriers to identify areas for improvement, fine-tune auction parameters, and optimize performance.
• Engage collaboratively. Lead successful collaborations with cross-functional teams including product managers, engineers, and data scientists to ensure seamless integration of modeling solutions within engineering systems.
• Innovate deliberately. Stay up-to-date with the latest advancements in machine learning, optimization techniques, and market dynamics to drive innovation and maintain a competitive edge.

What You'll Do

• Drive Market Mechanism Innovation:
  Enhance our auction mechanism to better match broker loads with carriers, tackling dynamic pricing, marketplace fairness, and efficiency at scale
• Develop AI-Powered Customer Experiences:
  Build and deploy next-generation AI products, including LLM-driven text and voice interfaces, for natural customer interactions
• Build Risk & Trust Systems:
  Create robust fraud detection and risk management models to maintain network safety and integrity
• Design Recommendation Systems:
  Deliver intelligent load recommendations using rich user behavior…