Research Scientist, Simulation & Decision Systems

This is a senior role for someone who wants to define how Atlas reasons about complex operational systems under uncertainty. You will shape the methods the platform uses, the way they are validated, and the standards we hold ourselves to as we grow.

• Define the methodological foundations for simulation, scenario projection, and decision support across the Atlas platform.
• Develop validation and calibration practices that let us, and our clients, trust the outputs of the system.
• Work with domain experts to translate operational reality into models Atlas can reason over.
• Design experiments and studies that clarify how the platform behaves under real operating conditions.
• Mentor the engineering team on statistical, probabilistic, and simulation reasoning.
• Publish internally. Publish externally where appropriate and where client confidentiality allows.

• Deep background in a relevant field: statistics, machine learning, operations research, simulation, or a related discipline.
• Track record of applied research that shipped into something real, not only into papers.
• Strong written communication. You will write more than you expect.
• Comfort working in an early-stage environment where the questions are not fully specified yet.

These are not required. They are the kind of background that tends to do well in this role.

• Experience with decision support in high-stakes domains with partial information.
• Prior work on explainable, auditable, or uncertainty-aware machine learning.
• Exposure to systems that have operated continuously in production for years.