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Principal Decision Scientist, Applied Optimization and Simulation 2026 - US, UK
Aimpoint Digital
Remote, USA
Full-time
Senior · 5+ years experience
Remote
Discovered 2 weeks ago
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What you will do
- As a part of Aimpoint Digital, you will focus on enabling clients to get the most out of their data. You will work with all levels of the client organization to build value driving solutions that extract insights and then train them on how to manage and maintain these solutions. Typical solutions will utilize machine learning, artificial intelligence, statistical analysis, automation, optimization, and/or data visualizations. A Principal Decision Scientist will define high-level business objectives directly with clients, then develop and execute the project plan to meet those objectives. You will proactively research and apply knowledge within the data science space to deliver best-in-class solutions. You will lead both small and large teams over the entire data science lifecycle – from problem definition to model automation and deployment. As a Principal, you will be expected to provide technical leadership to guide development work across teams while also owning and delivering specific technical components yourself. A Principal Decision Scientist will also manage all aspects of client relationships and create value-driving initiatives for the company.
Who we are looking for
We are looking for collaborative individuals who want to drive value, work in a fast-paced environment, and solve real business problems. You are a coder who writes efficient and optimized code. You are a problem-solver who can deliver simple, elegant solutions as well as cutting-edge solutions that regardless of complexity, your clients can understand, implement, and maintain. You genuinely think about the end-to-end solution pipeline as you generate robust solutions. You are both a teacher and a student as we enable our clients, upskill our teammates, and learn from one another. You want to drive impact for your clients and do so through thoughtfulness, prioritization, and seeing a solution through from brainstorming to deployment.
MS/PhD in Operations Research, Industrial Engineering, Computer Science, Mathematics, Engineering, or other STEM-related field
Strong theoretical knowledge of optimization techniques, including linear programming and integer programming and/or dynamic programming and graph theory
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