Sr. Analyst

  • 32996
  • Non-Life - CAT Modeling
  • |
  • California, United States
  • |
  • Oct 24, 2017
Software Organization
  • Researching and mining socio-economic and engineering information related to insured properties and other assets in various countries around the world.
  • Developing, evaluating, and implementing methodologies and solutions for property valuation and human exposure.
  • Evaluating the insurance policy language in the P&C industry in various countries and translating those details to implementable assumptions.
  • Developing insured value estimates, localized deductibles and limits, and similar data at different geographic resolutions such as Post Code, County, CRESTAs, District, and State.
  • Executing analytics of the Exposure Data provided by our clients, and benchmarking data products against such data.
  • MS or PhD degree in an engineering or science related field, including but not limited to: Civil and Structural Engineering, Urban Planning and GIS, Financial Engineering, Operations Research, Industrial Engineering, Applied Math, Econometrics, Actuarial, Science, and Statistics. PhD degree preferred.
  • Minimum 1 to 4 years of experience in the related industry. Some expreince in analytical or quantitative modeling in the insurance or a related industry is preferred.
  • High level of proficiency in data analysis and data manipulation software tools (including SQL, Excel, Access, and VBA).
  • Knowledge of GIS preferred, including experience with ArcGIS and QGIS.
  • Proficient programming skills in Python, R, or similar.
  • Experience in one or more of the following is desired: data mining, developing analytical models, developing data products, underwriting, claims handling, or Actuarial Analysis.
  • Proven record of developing analytical models is needed.
  • Excellent written and verbal communication skills, as evidenced by technical presentations at meetings and conferences.
  • Detail-oriented, ability to learn quickly, very strong analytical and organizational skills, and a high degree of self-motivation.
  • Project management experience, and the ability to work collaboratively with a team of colleagues across several groups and offices.