Improbable believes in a future where new, virtual worlds will augment human experience and become as meaningful, lasting and rich as the physical world.
Our platform, SpatialOS, lets developers transcend the limits of regular computation, allowing swarms of servers running in the cloud to cooperate in order to simulate worlds far larger and more complex than any single server could. The team in Arlington, VA is focused on applying our technology to solve real world problems within Government and Industry.
At Improbable, you are surrounded by people who want to improve everything and everyone around them, and who compel you to improve yourself. We’re motivated by the fulfilment of solving hard problems to achieve something profound and transformative.
is to build innovative, product-oriented solutions leveraging and contributing to our R&D effort around probabilistic techniques. We are growing our applied science capability to enable our federal customers to better understand their most challenging problems. Our applied scientists are delivery focused, working in diverse technical teams to design, build, deploy and evaluate models and simulations. You will work with customers to deliver new solutions to some of the most important challenges we face today.
We’ve already built a team of 15 highly experienced engineers, and scientists; now we’re moving onto the next chapter of our growth. We offer competitive salaries, full benefits, training, progression, equity and a chance to be a “founder“ of a strategically important new office.
Overview of our products here
You can read about the engineering culture of the division here.
- Prototype models, iteratively designing robust models that meet the needs of the client’s use case.
- Critically assess the type and quality of customer data and work with them to appreciate their toughest problems, define modelling assumptions and capture uncertainty.
- Work closely with our customers to develop a strategy to extract the maximum possible value from the available data
- Collaborate with engineers to build models in production environments.
- Be involved throughout customer interaction from project scoping to final delivery
- Work independently or with our research team to develop a modelling strategy to sit at the core of a data-led simulation-based approach to problem solving
- Take ownership of ensuring and demonstrating the reliability of the models that we create
Additionally you will drive thought leadership within the company and help our clients to understand their data needs and design their data strategies. This involves keeping up-to-date with a diverse body of cutting-edge research, designing and prototyping pioneering new technical approaches and rapidly developing expertise in new subject areas to support new bids and projects.
- Strong background and experience in delivery of technical, data-rich projects ideally for external clients.
- Degree in a scientific or mathematical field, ideally with a computational element
- Pragmatic coding ability - with fluency in at least one relevant programming language and the openness to learn and adapt to a variety of languages. We use Python, Pandas, R and many related tools and libraries.
- Enthusiastic about continuously improving and rapidly developing new competencies.
The following would be advantageous, but isn't essential
- Bayesian methods
- Effectively communicating and visualising analysis of rich data sets
- Probabilistic programming. You can see our early open-sourced work here.
- Working with real, complex data
- Effectively communicating with clients in person, in writing and with visualisation
- Our office is currently located in Arlington, VA with travel to client sites across N. Virginia
The best ideas are often the least expected and require new ways of thinking; that’s why our teams at Improbable are made up of an incredible range of talented people. Improbable is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy, childbirth, related medical conditions and lactation), sexual orientation, gender identity, gender expression, national origin, marital status, age, protected veteran or disabled status, genetic information, or any other legally protected status.