Applied Scientist at Improbable-2

Join our team at Improbable U.S. Defense & National Security and you will help customers use our synthetic environment development platform to plan and train for the most complex security threats in the world. Working alongside experts in AI, Machine Learning, computational modeling, and distributed systems, you will apply multiplayer gaming technology to life-saving purposes. Our mission is to create the most realistic and effective virtual worlds ever experienced. Our group in Arlington, VA, and at several other U.S. locations, focuses on turning that technology into practical solutions for Defense and National Security challenges. At Improbable you will work with colleagues who push themselves and each other to improve, driven by the satisfaction of solving difficult problems that lead to meaningful change.

What you'll be doing

• Combine leading models to design and refine Modeling & Simulation applications that address real customer needs.
• Build and test iterative prototypes of real-world systems so customers can examine past events, interpret current conditions, and anticipate future outcomes.
• Partner with engineers to move high-performance models into production environments while collaborating with the product team to strengthen our core technology platform.

What you'll bring

• A strong record of delivering technical, data-intensive projects, preferably for external clients.
• A degree in a scientific, engineering, or mathematical discipline, ideally with a computational focus.
• Proven experience in statistical modeling and analysis, along with work in agent-based modeling, micro-simulation, computational social science, or socio-technical systems.
• Hands-on experience with game engines such as Unity or Unreal.
• Practical coding skills with fluency in at least one relevant programming language and the willingness to learn others; our stack includes Python, R, Java, C, and C++.
• Ability to break down complex requirements, choose suitable analytical methods, and produce well-supported solutions.
• Familiarity with probabilistic programming and working with complex, real-world data, including geospatial datasets.
• Clear communication with clients through meetings, written reports, and data visualizations.
• English language proficiency.

What you'll get

• Hybrid work arrangements.