Principal Decision Scientist, Applied Optimization, Simulation

Aimpoint Digital

. Enable Federal clients to get the most out of their data .

Posted 9/29/2026full-timeAtlanta • United StatesLeadWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and building end-to-end analytical solutions, utilizing Python and optimization techniques to solve complex decision science use cases. Proven ability to lead projects, mentor junior team members, and effectively communicate insights to stakeholders.

Highest-signal resume keywords

Python ProgrammingOptimization TechniquesEnd-to-End Model DevelopmentDecisionOps/MLOps PracticesFederal Client Experience

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Mathematical OptimizationStatistical ModelingFeature EngineeringMachine LearningData ManipulationLinear ProgrammingInteger ProgrammingDynamic ProgrammingGraph TheoryModel Deployment

Soft Skills

Strong Communication SkillsLeadershipMentoringSelf-StarterCollaboration

Tools & Technologies

AIMMSAMPLGAMSPyomoGurobiCPLEXXPRESSDatabricksSnowflake

Certifications & Qualifications

Databricks Machine Learning CertificationSnowflake SnowPro CertificationClaude Certification

Industry Keywords

Decision ScienceAgentic WorkflowsSIPR AccessFederal ClientsConsulting Experience

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Enable Federal clients to get the most out of their data
Design and build end-to-end analytical solutions from solution architecture through feature engineering, modeling, deployment, and maintenance
Solve complex decision science use cases using mathematical optimization, simulation, machine learning, statistical/mathematical modeling, and analytics
Build and manage agentic workflows for modeling tasks
Lead projects ranging from hands-on single-developer engagements to complex multi-team projects
Coordinate between account management and development teams
Manage and mentor junior decision scientists
Synthesize insights and construct narratives to influence decision-making
Write Python code using software engineering best practices
Move models from development to production in client environments following DecisionOps/MLOps practices
Collaborate with stakeholders and customers to ensure successful project delivery
Assist with technical proposal and go-to-market material development
Contribute to Aimpoint’s perspective on agentic and AI-accelerated decision science
Lead and deliver internal practice development initiatives

Requirements

What you’ll need

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 another STEM-related field
MS plus 5-6 years of practical experience
PhD plus 4-5 years of practical experience
Strong theoretical knowledge of optimization techniques, including linear programming, integer programming, dynamic programming, and graph theory
Proficiency in Python and/or optimization platforms such as AIMMS, AMPL, GAMS, or Pyomo
Practical experience with open-source and commercial solvers such as Gurobi, CPLEX, or XPRESS
Competency in Python for data manipulation and modeling via classical machine learning methodologies
Demonstrated end-to-end model development experience, including requirements gathering, solution design/architecture, EDA/data validation, model development/testing, deployment, maintenance, and business-user handoff/training
Experience communicating complex topics and results to high-level stakeholders
Strong written and verbal communication skills
Self-starter able to work independently and lead projects, initiatives, and/or people
Consulting experience, Databricks Machine Learning certification, Snowflake SnowPro certification, Claude certification or agent-generation experience, and Federal client experience are differentiators

Benefits

Comp & perks

Full-time remote work within the US
Opportunity to work on impactful Federal client projects
Career development through mentoring and upskilling
Opportunity to contribute to practice development and business development
Opportunity to work with AI, machine learning, optimization, simulation, and analytics technologies