Our 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.
We are building the methods and technology to realise a step change in decision support, planning and collective training, through the use of agent-based modelling, digital twins and optimisation.
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.
- 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.
- Investigating third-party data sources and products, evaluating their applicability and assisting in the creation of pipelines to make them available to simulation engines and user interfaces.
- Keeping our standards high, reviewing development work, infrastructure and processes to be a champion of best practice within the team, so our customers can be confident in the solutions we deliver.
- Critically evaluating the results of simulations and presenting these back to key stakeholders & decision makers, while adapting your communication style to the relevant audience.
- Spending time with our customers to understand their perspectives and inform their thinking as we create new products for defence.
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, machine learning, optimisation or Bayesian statistics.
- Enjoy developing models from first principles and are unbiased in your choice of modelling techniques
- Experience across the whole lifecycle of a model including requirements gathering, converting these into actionable tasks, model implementation, validation and deployment.
- Ability to conduct research, produce conceptual models, develop prototypes and mentor others in the process.
- Experience communicating complex modelling concepts to a range of audiences both technical and non-technical.
- Experience assuming a technical leadership role on projects.
- 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.
