Statistical Data Analyst/R Programmer
The Statistical Data Analyst/R Programmer role is to analyze data from different perspectives and summarize it into useful information to support and enhance the insurance and third party administrator (TPA) operations of Key Risk. As part of the Actuarial Department of Key Risk, this individual will work with multiple operating departments (including but not limited to Underwriting, Claims, Risk Management, Marketing, Finance and Alternative Risk Services) to develop understand their needs and objectives and to provide solutions to help meet those objectives.
This individual will work closely with the Information Systems (IS) department and other Business Intelligence (BI) power users in the development of business intelligence tools for the organization which will include utilization of the data warehouse and creation of data marts as needed.
- A Bachelors level college degree (or higher) in Statistics, Mathematics, Insurance and Risk Management, or other related fields (Finance, Economics, Computer Science);
- Must possess basic knowledge of statistical practices and concepts including but not limited to: appropriate data collection to produce valid conclusions, correlation analysis, multivariate regression analysis, factor analysis, principle component analysis, cluster analysis, bootstrapping and data simulation;
- At least one year of extensive experience with using the statistical programming language R;
- Must be an advanced user of (1) spreadsheet and database related applications such as MS Excel, Oracle, Hyperion, MS Access and/or FoxPro, (2) SQL or other advanced data extraction tools or programming languages and (3) word-processing software such as MS Word;
- Must be able to work independently, apply critical thinking during the course of projects, and possess the ability to handle multiple projects simultaneously;
- Strong written and verbal communication skills are required including the ability to compose non-routine reports, graphs, and memos for a diverse audience;
- The ability to communicate the results of complex material to both a technical and non-technical audience;
- Preference given to candidates with Data Mining or Predictive Modeling experience.
- Report directly to the Chief Actuary;
- Understand the Company operating systems and how to access and develop reports with data from both a data warehouse and mainframe environment;
- Work with IS to implement efficient use of the data warehouse in developing data analysis programing and tools;
- Provide more complex programming as needed to access and organize data without appreciable direction;
- Develop a library of programs using R and other available software for data analysis, including research of current code available in the CRAN library of packages;
- Work with various operational areas of the Company to develop a strong understanding of the how the various functional aspects of the operations might be reflected in the data;
- Conduct research using company specific , industry and other available data to enhance and improve operating efficiency and leverage unique aspects of the Company to improve profitability and market position;
- Develop a deeper understanding of the technical, actuarial, insurance, economic, and statistical concepts behind the task performed. Use knowledge to review reasonability of results of research;
- Effectively communicate these results to a wide audience including senior leadership and operational management;
- Develop a strong insurance skill set by actively participating in continuing education such as statistical and data analysis seminars and/or the CPCU exam process.
Indeed - 17 months ago