Applied Scientist at Improbable-2

At Improbable U.S. Defense & National Security, we develop a synthetic environment platform that helps defense and national security organizations plan and train for complex, high-stakes threats. Our teams in Arlington, Virginia, and additional U.S. locations combine expertise in artificial intelligence, machine learning, computational modeling, and distributed systems to turn advanced multiplayer gaming technology into practical tools for mission-critical work. We are now seeking a senior applied scientist to strengthen these efforts and deliver models and simulations that address real-world operational challenges.

Key outcomes

• Integrate leading models to design and refine modeling and simulation solutions that meet customer requirements.
• Design and prototype models of real-world systems that allow users to examine past events, assess current conditions, and anticipate future developments.
• Partner with engineers to move high-performance models into production environments.
• Collaborate with the product team to improve the underlying technology platform.
• Evaluate customer and open-source data, establish modeling assumptions, and quantify uncertainty.
• Ensure and demonstrate the reliability of the models developed for each project.
• Engage directly with customers to understand their operational problems and shape appropriate use cases for our technology.
• Provide technical leadership by tracking emerging research, prototyping new approaches, and rapidly building expertise in new domains to support proposals and projects.

Requirements

• Proven experience delivering technical, data-intensive projects, preferably for external clients.
• Degree in a scientific, engineering, or mathematical discipline, preferably with a computational focus.
• Strong knowledge of statistical modeling and analysis.
• Experience with agent-based modeling, micro-simulation, computational social science, or modeling socio-technical systems.
• Hands-on experience with game engines such as Unity or Unreal Engine.
• Practical programming skills with fluency in at least one relevant language and the ability to learn additional languages as needed; our stack includes Python, R, Java, C, and C++.
• Ability to analyze complex problem statements, select appropriate analytical techniques, and produce well-supported solutions.
• Familiarity with probabilistic programming techniques.
• Experience working with complex, real-world data sets, including geospatial data.
• Clear and effective communication skills for client interactions, written reports, and data visualizations.
• Professional working proficiency in English.

Preferred qualifications

• Additional experience across multiple programming languages and related libraries beyond the core requirements.
• Background contributing to open-source probabilistic programming projects.

Compensation

We offer a hybrid work arrangement that supports both in-office collaboration and remote flexibility.

How to apply

If your background and interests align with this opportunity, we invite you to submit your application. We welcome candidates who share our mission even if their experience does not match every listed requirement.