Applied Scientist, Modelling and Decision Science


Join our defence and national security business and you’ll be helping users plan and train to meet the most complex security threats in the world. Working alongside experts in AI and Machine Learning, computational modelling and distributed systems, you’ll be putting multiplayer technology to life-saving use.
Your goal is to provide the scientific models that sit at the heart of our core product offering. This means building data pipelines to generate accurate representations of real-world environments as well as algorithms for simulating their dynamics.
We take agent-based modelling to the next level in terms of extensibility, fidelity and scientific validity and we model social systems as goal-oriented actors operating on imperfect information. We 'digitally twin' physical environments and infrastructure and obsess about modularity in order to recast complex systems as combinations of simpler components. Our applied scientists seek to balance innovation with pragmatism, all while maintaining an awareness of the state-of-the-art.

Areas of Impact:

  • Leading the creation of scientific models for our product, ensuring that customers have the functionality they need now and in the future. This will involve a combination of supporting, mentoring and leading applied scientists in conducting literature reviews, conceptual modelling and prototyping as well as being hands-on in the process of model creation and deployment yourself.
  • Working with product and delivery teams to interpret technical requirements and formulate them into applied science tasks, whilst working alongside other applied scientists to deliver them.
  • Working with designers to create scientific workflows which enable military analysts and planners to effectively run scenarios and view valuable insights for decision support.
  • Critically evaluating the results of simulations and presenting these back to key stakeholders & decision makers, while adapting your communication style to the relevant audience.
  • Telling a story with the data from our products and simulations, remaining pragmatic about their limitations and providing a realistic view to colleagues, stakeholders and clients of the benefits and risks inherent to data-driven decision making.

We’d like to hear from you if you identify with the following:

  • You have experience with a range of modelling paradigms and techniques such as agent-based modelling, monte-carlo modelling, discrete event simulation, decision trees, machine learning, optimisation or Bayesian statistics
  • Enjoy developing models from first principles and are unbiased in your choice of modelling techniques
  • Experience in conducting large scale simulation experiments to support strategic, operational and tactical decision making activities using an evidence-based approach. 
  • Experience communicating complex modelling concepts to a range of audiences both technical and non-technical
  • You have implemented models to high standards of engineering, either by yourself or by closely collaborating with engineers
  • You have a good first degree in a STEM subject with a significant mathematical component. A PhD is not required but is an advantage
  • Programming skills in Python

  • While we think the above experience could be important, we’re keen to hear from people that believe they have valuable experience to bring to the role. If you identify with the team and mission, but not all of our requirements, then please still apply.


About Us

Improbable is determined to foster an environment where people can do their best work and feel like they belong. We believe a healthy culture, strong values and contribution from a diverse range of individuals will help us to achieve success.
We do not discriminate based on race, ethnicity, gender, ancestry, national origin, religion, sex, sexual orientation, gender identity, age disability, veteran status, genetic information, marital status or any other legally protected status.

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