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. This role aims to solve challenging problems in digital logistics, such as matching supply with demand at scale, allocating resources efficiently under uncertainty, and building systems that can make and refine complex decisions.
Requirements
- Expert-level proficiency with Python and production-grade machine learning frameworks (PyTorch, TensorFlow, scikit-learn), with hands-on experience in large language models (LLMs), retrieval-augmented generation (RAG), and modern natural language processing (NLP) toolkits
- Demonstrated ability to build, deploy, and monitor both classic and generative AI models in real-world systems, with comfort working with APIs, microservices, and data pipelines
- Proven track record of translating ambiguous business problems into automated, scalable decision-making tools with a bias for action and operational excellence
- You have experience with two-sided marketplaces, financial markets, and economic theory
- You have built and maintained mature production ML models in large, complex systems
- You have applied foundational or cutting-edge research, especially in NLP, LLMs, reinforcement learning, or optimization, to unlock real-world business value
- You have experience in freight, logistics, or transportation technology
Responsibilities
- 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
- Drive Market Mechanism Innovation: Enhance our industry-leading 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, enabling customers to interact more naturally through chat, voice assistants, and automated workflows
- Build Risk & Trust Systems: Create robust fraud detection and risk management models to maintain the safety and integrity of our network
Other
- Set technical direction, mentor other scientists, and deliver solutions whose impact scales across teams and the broader Convoy Platform, not just within individual projects.
- Engage collaboratively with cross-functional teams, including product managers, engineers, and data scientists, to ensure seamless integration of the modeling solutions within the Engineering systems.
- Stay up-to-date with the latest advancements in machine learning, optimization techniques, and market dynamics to drive innovation and maintain a competitive edge.
- Ph.D. or MS in Computer Science, Statistics, Applied Mathematics/Operations Research, Engineering, or related quantitative field
- Minimum of 7+ years of experience developing and deploying machine learning solutions in production environments
