Improbable builds world-leading simulation technology that helps resolve previously impossible problems. Our technology platforms enable the creation of enormous virtual worlds for training and highly accurate "system of systems” simulations of complex real-world scenarios to facilitate better decision-making.
The Enterprise division of Improbable was formed in 2015. It seeks to create an Optimized World, where simulations of unprecedented scale and complexity provide insights into all of the most important problems faced by businesses and governments. The decisions based on this work will make a safer, more efficient and more prosperous world.
This process is enabled by distributed computation and the abundance of data generated by the digitization of the physical world. We believe that these huge simulations will be the next fundamental technology of our time. You can read more about our story here.
Our US engineering office is located in Arlington, VA
We are building a new data science and machine learning capability to enable our customers to better understand their most challenging problems. Our applied data scientists are delivery focused, working in diverse technical teams to design, build, deploy and evaluate data models. Our simulations are currently solving problems in industries as diverse as telecoms, urban planning and governance, training and more.
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.
- Work closely with our customers to develop a strategy to extract the maximum possible value from the available data
- Leverage the Python Data Science ecosystem to create prototypes, pipelines and visualizations to help our customers make better decisions. We also use R when necessary.
- Be involved throughout customer interaction from project scoping to final delivery
- Critically assess the type and quality of customer data and work with them to appreciate their toughest problems
- 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 mainly use Python, Pandas and many related tools and libraries.
- Enthusiastic about continuously improving and rapidly developing new competencies.
The following would be advantageous, but isn't essential
- Working with large data sets and big-data technologies such as Spark
- Bayesian methods
- Effectively communicating and visualising analysis of rich data sets
- Probabilistic programming
Our office is currently located in Arlington, VA with 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.