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Open nowPosted 4 days ago

Principal Decision Scientist, Applied Optimization and Simulation 2026 - US

Aimpoint Digital18 open roles

Where
Atlanta, Georgia, United States, Remote
Work mode
Remote
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Your applicationOpen nowPrincipal Decision Scientist, Applied Optimization and Simulation 2026 - USAimpoint Digital · Atlanta, Georgia, United States, Remote

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  5. 34.1%30 days
This job: posted 4 days ago

The posting

Aimpoint Digital is an AI and data consulting firm that turns AI ambition into production reality, built on the data and analytics foundation required to scale. This position is within our decision sciences practice which focuses on delivering production solutions via mathematical optimization and machine learning for our Federal customers. This role requires an active security clearance and a willingness to work on SIPR 2-4 days per week depending on project needs.

What you will do

As a part of Aimpoint Digital, you will focus on enabling our Federal clients to get the most out of their data. Our Decision Science practice focuses on business, data, and process understanding to identify the best approach to solve our client’s complex problems. We focus on delivering tangible value with models in production, not chasing theoretical boundaries with prototypes. Typical solutions will utilize machine learning, artificial intelligence, statistical analysis, automation, optimization, and data visualizations. As a Lead Decision Scientist you will be expected to work independently on client engagements, manage tasking for more junior decision scientists, take part in the development of our practice, aid in business development, and contribute innovative ideas and initiatives to our company. As a Lead Decision Scientist you will:

  • Become a trusted advisor working with clients to design and build end-to-end analytical solutions from initial solution architecture design through feature engineering, modeling, deployment, and maintenance
  • Work independently to solve complex decision science use-cases across various industries using mathematical optimization, simulation, machine learning, statistical/mathematical modeling, and analytics to solve use cases for our federal clients
  • Use your experience with decision science to build and manage agentic workflows to complete modeling tasks
  • Flexibly lead projects, from hands-on single developer engagements through complex projects coordinating between account management and a team of developers across Aimpoint
  • Manage or mentor junior decision scientists through their career at Aimpoint
  • Synthesize insights and construct narratives to influence decision making using optimization, simulation, statistics, ML modeling, and other techniques
  • Write code in Python following software engineering best practices
  • Take models from development to production in client environments following DecisionOps/MLOps best practices
  • Collaborate with stakeholders and customers to ensure successful project delivery
  • Assist with technical proposal and GTM material development
  • Contribute to the Aimpoint perspective on agentic and AI accelerated decision science
  • Lead and deliver internal practice development initiatives

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 uses AI to write 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 machine learning 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. In particular you have these traits:

  • Active Secret or higher security clearance
  • Willingness and ability to work on-site in a facility with SIPR access for 2-4 days per week
  • MS/PhD in Operations Research, Industrial Engineering, Computer Science, Mathematics, Engineering, or other STEM-related field
  • MS + 5-6 years practical experience
  • PHD + 4-5 years practical experience
  • Strong theoretical knowledge of optimization techniques, including linear programming and integer programming and/or dynamic programming and graph theory
  • Proficiency in a programming language such as Python, and/or proficiency in an optimization platform, AIMMS/AMPL/GAMS/Pyomo
  • Practical experience with open-source solvers and commercial solvers, such as Gurobi, CPLEX or XPRESS
  • Required competency in Python for data manipulation and modeling via classical ML methodologies
  • Demonstrated evidence of experience with end-to-end model development including but not limited to:
  • Requirements gathering
  • Solution design / architecture
  • EDA / data validation
  • Model development and testing
  • Model deployment
  • Model maintenance
  • Business user handoff / training
  • Experience communicating complex topics and results to high-level stakeholders. Strong written and verbal communication skills are required.
  • Self-starter with excellent communication skills, able to work independently, and lead projects, initiatives, and/or people

Want to stand out?

  • Consulting Experience
  • Databricks Machine Learning Associate or Machine Learning Professional Certification
  • Snowflake SnowPro Core Certification or SnowPro Advanced: Data Scientist Certification
  • Claude certification or experience to generate skills / agents for decision science tasks
  • Experience with mathematical optimization and data science for Federal clients

We are actively seeking candidates for full-time, remote work within the US.

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