Risk Management Solutions (RMS) is the world's leading provider of mathematical models and information related to the financial impact of catastrophes. Our Model Development department has over fifty PhD scientists and engineers based in London, building mathematical models which predict the distributions of possible damage due to catastrophic events, both natural (e.g. earthquakes, storms, floods), and man-made (e.g. cyber threats, terrorist attacks, pandemics).
Our clients include several hundred insurance and reinsurance companies as well as brokers, banks, hedge funds, regional and local governments, and multilateral agencies.

JOB DESCRIPTION
* Position Summary
Within Model Development, the Cyber Risk Modelling team is tasked to develop world-class risk models for the emerging cyber threats, thus providing comprehensive solutions to our Clients.
The purpose of this role is to develop tools and capabilities to understand organisations’ cyber risk, and to develop metrics and models to quantify the risk which cyber events pose to an insurance portfolio.
It presents a unique opportunity to work on novel modelling ideas and methods which can have a real impact in the medium and longer term development of cyber risk markets. This is further enabled by RMS’ central position as a lead provider of scientific understanding and quantification of catastrophic digital risk. 

* Essential Job Functions
The successful applicant will assemble and use large and complex datasets to extract and manipulate data during the development of sophisticated risk models. S/he will use various modelling techniques to quantify the impact of cyber risks (e.g. data breaches, contagious malware, DDoS, financial theft, extortion, and so on) to organisations. In addition, s/he will be expected to contribute to team discussions on development of cyber catastrophe modelling methods.
The objectives during the first several months include:
- Understand data sources of cyber threat incidents and assess their quality and quantity
- Collect, cleanse, organize and curate relevant data sets
- Apply appropriate modelling methodologies to extract conclusions on identity, taxonomy, frequency, severity and interdependency of cyber threats
- Establish iterative workloads for efficient and scalable ETL and modelling

* Minimum Qualifications
The ideal candidate’s qualities, skills and attributes follow. Please provide your CV highlighting the salient education and experience, and a cover letter demonstrating how these meet the requirements of the position.
- PhD or MSc degree in a relevant subject; for example, applied mathematics, computer science, data science, statistics, actuarial science, engineering, or physical sciences.
- Strong mathematical foundation with particular focus on mathematical statistics and probability.
- Experience working on large and complex datasets including ones stored in relational databases.
- Demonstrated success in developing sophisticated models using advanced mathematics, statistics, or data science in industrial or academic environments.
- Strong ability in modelling languages such as R and Python.
- Previous experience in 1) cyber risk assessment and analysis, and 2) modelling economic impacts of disasters.

* Preferred Qualifications
- Knowledge and experience with advanced methods of actuarial modelling.
- Experience in Bayesian data analysis, including familiarity with machine learning.
- Strong user skills in a Linux/Unix environment (bash, csh, awk and sed, perl, python).
- Familiarity and interest in big data relational databases like Apache Spark SQL.
- Excellent time management and planning skills with a commitment to delivery.
- Driven and committed, demonstrating initiative and self-motivation.
- Critical thinking and problem solving skills.
- Attention to detail and intense curiosity.
- Willingness to pursue continued education in support of the role and team goals.

*About RMS:
There’s a 5% chance that a hurricane will cause $60 billion of insured losses next year and a 1% chance an earthquake will cause $50 billion of insured loss in the next 12 months. 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 companies you’ve probably ‘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.

RMS has 1,200 employees in 11 countries, including offices in Newark (CA-USA), Noida (India), London (UK), Hoboken (NJ-USA), and Zurich (Switzerland). To find out more, visit www.rms.com or follow us on Facebook, LinkedIn or @rmsjobs on Twitter.

RMS is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity without regard to race, color, creed, gender, religion, marital status, registered domestic partner status, age, national origin or ancestry, physical or mental disability, genetic characteristics, sexual orientation, or any other classification protected by applicable local, state, or federal law.

RMS is enrolled in E-Verify® and will be participating in E-Verify in addition to our Form I-9 process. www.dhs.gov/E-Verify.

To all recruitment agencies: RMS does not accept unsolicited agency resumes and will not responsible for the payment of placement fees related to unsolicited resumes submitted to open positions, job aliases, or to our employees.

Christos Mitas, PhD
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