Staff Research Scientist, Trucking

Solve the world's most challenging problems in the Trucking industry with data

Flexport Trucking seeks a visionary and technically exceptional Staff Research Scientist to solve some of the most ambitious challenges in the $800B U.S. freight industry. We’re building the next-generation Convoy Platform, the nation’s leading digital freight network, to make truckload movement smarter, greener, and more efficient for brokers and carriers nationwide.

At the heart of Flexport Trucking, the Convoy Platform leverages cutting-edge technology to intelligently connect freight with capacity. Our digital marketplace enables brokers, and carriers to collaborate and transact seamlessly, reducing costs, maximizing driver earnings, and minimizing waste. This is your chance to tackle intricate, high-impact problems at the intersection of logistics, AI, and large-scale systems.

As a Staff Research Scientist, you will play a critical role in developing data-driven products and platforms that power our two-sided marketplace. You’ll partner closely with Engineering, Product, and Data Science, driving research and innovation in areas such as:

• Market Mechanism Design:
  Enhance our industry-leading auction platform to better match brokers and carriers, tackling dynamic pricing, marketplace fairness, and efficiency at scale.
• AI-Powered Experiences:
  Develop and deploy next-generation AI products, including LLM-driven text and voice interfaces, enabling customers to interact more naturally and flexibly via chat, voice assistants, or automated workflows.
• Risk & Trust Systems:
  Build robust fraud detection and risk management models to maintain the safety and integrity of our network.
• Recommendation Systems:
  Deliver intelligent matching and load recommendations, optimizing carrier and broker success
• Causal Inference & Experimentation:
  Design and analyze experiments to accurately measure the impact of new features and pricing strategies across our marketplace.
• Product Optimization:
  Apply machine learning, optimization, and econometrics to continually refine marketplace processes, pricing, and customer insights—fueling smarter products that shape the future of freight.

You will:

As a Staff Research 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 you’re using collaborative filtering to generate highly personalized load recommendations, enhancing those recommendations with a conversational AI agent powered by LLMs to deliver actionable offers to carriers, or reimagining auction mechanisms with cutting-edge reinforcement learning, your mandate is to identify and apply the right algorithmic and data-driven approach to maximize the impact of every feature. You’ll drive innovation across the Convoy Platform, always seeking new ways for our systems to make smarter, faster, and more reliable decisions.

Develop feedback-aware automated decision-making systems
There are many situations where models simply do not outperform humans. We are looking for individuals who are open to building systems capable of ingesting human inputs. This means as part of the role, you will continuously analyze feedback from brokers and carriers to identify areas for improvement, fine-tune auction parameters, and optimize performance.

Engage collaboratively
Science drives automated decisions across many domains at the Convoy platform. We seek individuals with a history of leading successful collaborations with cross-functional teams, including product managers, engineers, and data scientists, to ensure seamless integration of the modeling solutions within the Engineering systems.

Innovate Deliberately
We’d like the individuals joining our team to stay up-to-date with the latest advancements in machine learning, optimization techniques, and market dynamics to drive innovation and maintain a competitive edge.

You should have:

• Leadership and Domain Experience
  Ph.D. or MS in Computer Science, Statistics, Applied Math/OR, Engineering, or related quantitative field with a minimum of 7+ years of experience developing machine learning solutions.
  
  
• Technical Aptitude
  Proficiency with Python and production-grade machine learning frameworks (such as PyTorch, TensorFlow, or scikit-learn), and experience with 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, and comfort working with APIs, microservices, and data pipelines.
  
  
• Technical Problem Solving
  Proven track record of translating ambiguous business problems into automated, scalable decision-making tools. A bias for action, love for simplicity, and a knack for balancing experimentation with operational excellence.
  
  

A plus if you have experience in 

• Two-sided marketplaces, financial markets, and economic theory.
• Building and maintaining mature production ML models in large, complex systems.
• Applying foundational or cutting-edge research—especially in NLP, LLMs, reinforcement learning, or optimization—to unlock real-world business value.

Successful Flexporters share these traits:

• We’re passionate about solving complex problems and get excited about diving deep to understand an issue.
• Our titles don’t define us, we do what’s needed to prioritize our customers.
• We support others through change and uncertainty and stay the course when things get challenging.
• We believe in our mission and the potential for impact in our space.

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