Data Scientist

This is a fully remote position, open to applicants in Virginia.

📋 Description

• Create and execute optimization models, including mixed-integer linear programming and constraint programming, for distributing limited parts and resources among competing programs.

• Develop machine learning models to anticipate demand, assess supply risk, and determine part availability.

• Convert conflicting program priorities into formal objective functions and constraints.

• Validate model outputs against historical allocation decisions and stakeholder expectations.

• Refine model formulations as new constraints arise.

• Construct and manage data pipelines utilizing live inventory, demand, and program data.

• Present modeling trade-offs and recommendations to non-technical program and supply chain stakeholders.

• Mentor junior data scientists on optimization methods and modeling best practices.

• Collaborate with software engineers to implement models as scalable services.

• Oversee the entire modeling lifecycle from problem formulation and data exploration through to validation and production deployment.

⛳️ Requirements

• Master's or PhD in Operations Research, Applied Mathematics, Computer Science, Industrial Engineering, or a related quantitative field (or equivalent practical experience).

• Over 6 years of experience in developing optimization and/or ML models for resource allocation, scheduling, or supply chain challenges.

• Extensive hands-on experience with optimization solvers such as Gurobi, CPLEX, or OR-Tools.

• Proficient in formulating MILP and constraint optimization problems.

• Strong proficiency in Python.

• Experience with machine learning frameworks like scikit-learn and PyTorch.

• Familiarity with pandas and NumPy.

• Experience dealing with messy, real-world supply chain, inventory, or program data.

• Exceptional communication skills and comfort in presenting complex trade-offs to program and business stakeholders.

• Preferred: experience with allocation challenges in aerospace, defense, or manufacturing supply chains.

• Preferred: knowledge of ERP systems such as SAP.

• Preferred: experience in deploying optimization models as production services, APIs, or batch pipelines.

• Preferred: exposure to reinforcement learning or Bayesian methods for making decisions under uncertainty.

🏝️ Benefits

• Remote work arrangement.

• Continuous learning opportunities.

• Inclusive and collaborative culture.

• Mentorship opportunities.