About the job
In this role, you'll sit at the intersection of state-of-the-art research and real-world impact. You will design and build algorithms that solve large-scale, complex logistics problems, synthesize data from diverse sources to identify high-value business opportunities, provide research direction and data-driven insights to guide strategic decisions, translate complex technical approaches into clear communication for scientists, engineers, and business stakeholders, and partner closely with scientists and engineers in a collaborative, high-impact environment.
Responsibilities
Invent and design novel solutions for scientifically complex problem areas, and identify opportunities for invention within existing and new business initiatives
Deliver large-scale, high-impact solutions to complex problems in support of medium-to-large business goals
Shape the design of scientifically complex software systems, personally contributing significant portions of the critical scientific novelty
Apply mathematical optimization, machine learning, and Generative AI techniques to develop solution methodologies for in-house decision support tools and software
Research, prototype, simulate, and experiment with models — and actively participate in their production-level deployment in Python or Java
Engage with the broader scientific community by publishing research articles and participating in leading research conferences
Qualifications
Minimum
Deep expertise in Operations Research and/or Machine Learning methods
Proven experience applying these methods to large-scale, real-world business problems
Ability to translate models into production-ready code in Python or Java
Strong communication skills — you can explain complex technical concepts to diverse audiences
A bias for action and an iterative mindset when tackling ambitious research challenges
Preferred
PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field
Experience in patents or publications at top-tier peer-reviewed conferences or journals
3+ years of solving business problems through machine learning, data mining and statistical algorithms experience
3+ years of mathematics optimization such as linear programming and nonlinear optimization experience