|From||"Roger Brugge" <email@example.com>|
|Date||Wed, 15 May 2013 12:55:01 +0000|
Scientific Programmer (Senior Modeler), Model Development, London Department: RMS Model Development (MDev) boasts a team of around eighty scientists based across London (UK) and Newark (California) building mathematical models that predict the distribution of possible damage due to the effects of natural (e.g. earthquakes, tropical and extra-tropical storms, thunderstorms, storm-surges and fluvial floods), as well as man-made (e.g. terrorist attacks) catastrophic events. Within our RMS MDev group, the Cross Peril Methodology (CPM) team is responsible for developing scientifically robust methods across all our models, and for ensuring that the software developed to enable these methods is of the highest quality. We are looking to hire a Scientific Programmer into our London team at the level of Senior Modeler. Objective of the role: Understanding the mathematical modeling ideas developed at RMS and being able to express them clearly and efficiently within the software framework which RMS Software Development team (SDev) is building for RMS(one). As our team grows, there will be scope for personal advancement, including future leadership opportunities in both modeling and software development. Key Responsibilities: • Collaborating closely with our core model developers across all our hazard, exposure, and vulnerability teams, in a dynamic and business driven environment; • Developing new code and modifying against specific modeling requirements; • Explaining as well as promoting the latest and most innovative software development techniques to the mathematical modeling team. • Some international travel (mainly to our RMS Head-Quarters in Silicon Valley, CA). Qualifications and Skills: Essentials: • PhD or MSc in Mathematics, Science, Engineering, or Computer Science gained at a leading Russell Group University or equivalent; • Excellent programming skills, including C#, C++, and .NET is essential; • Proven & Successful experience in developing scientific applications with such tools; • Excellent communication and prioritization skills. Desirables: • Analytical mindset and strong programming skills in a Linux/Unix environment (Fortran, R, bash, csh, python, awk and sed). Experience working on large data sets in such an environment; • Experience working with relational databases such as SQL Server, MySQL, as well as using NoSQL databases such as MongoDB, Cassandra, HBase; • Understanding of Software Development Life Cycle processes, as well as Agile development methodology; • Application development experience in a Cloud environment preferred. RMS: Did you know there’s a 5% chance that a hurricane will cause $60 billion of insured losses next year? And there’s a 1% chance that an earthquake will cause $50 billion of insured loss in the next 12 months? We do. At RMS, we build the simulation models that allow insurers and investors to understand portfolio risks due to catastrophes: natural catastrophes (hurricane, earthquake, flood), terrorism, pandemic, and changes in life expectancy. We are one of the most exciting and technologically sophisticated firms you’ve "never" heard of, unless you’re one of our hundreds of clients in the (re)insurance, banking or hedge fund sector. We lead an industry we helped pioneer and ultimately our work makes a true impact on the world at large. How we understand and manage risk affects everybody and our passion is nothing less than creating a more resilient world through a better understanding of catastrophic events. As we approach our 25th anniversary, we are now evolving our vision by delivering future solutions in the cloud, releasing in 2014 a cutting edge risk management platform "RMS(one)" for the global risk market. RMS(one) will create a holistic and integrated view across the enterprise with one platform for all models, all points of view, all data. All will be run as equal partners on RMS(one). To find out more, visit www.rms.com Or follow us on Facebook or @rmsjobs on Twitter RMS is proud to be an equal opportunity employer.
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