DATA SCIENCE MANAGER at National General
Responsible for leading the development and implementation of homeowner’s predictive models for our growing Preferred and Premier Homeowner’s product lines.
Essential Duties and Responsibilities:
Following is a summary of the essential functions for this job. Other duties may be performed, both major and minor, which are not mentioned below. Specific activities may change from time to time.
- Build predictive models using GLM, logistic regression, and other means, in support of creation and implementation of new rating plans and other initiatives.
- Work collaboratively with team members to execute on all aspects of model development, including data extraction/ data load, data cleansing, variable creation, and model building.
- Develop and implement models for insurance loss, conversion, retention, and price optimization.
- Monitor the performance of current models that are in place and recommend changes to models.
- Design and manipulate large datasets across platforms.
- Identify new opportunities to leverage analytics within the company.
- Analyze new data sources for availability and quality, and integrate with internal sources to support research or analytics.
- Participate in presentations to business users.
- Participate in the training and development of staff and manage projects from research design through conclusions and recommendations.
Minimum Skills and Competencies:
The requirements listed below are representative of the knowledge, skill and/or ability required. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
- Bachelor Degree or in-lieu of degree equivalent education, training and work-related experience
- 5+ years of experience in an analytics driven role
- 1+ years of experience managing people and projects
- Strong programming skills, specifically in SAS, SQL, and R
- Strong programming expertise in data manipulation using SAS (or SQL in a similar analytics/database package, such as SQL server)
- Expertise with predictive modeling software including R and Python
- Experience with insurance predictive modeling, specifically homeowners products
- Must possess effective verbal and written communication skills
- Proficient in Microsoft Office (Word, Excel, Outlook, PowerPoint)
- Bachelor Degree, Master Degree or higher degree in Statistics, Mathematics, Computer Science, Economics, Actuarial Science, or other related field of study
- Actuarial designation (ACAS, FCAS, CSPA)
- 3+ years of insurance industry experience
- P&C insurance industry background with working knowledge of homeowner's insurance
- Understanding of insurance product design and mathematical underpinnings of rating algorithms
- Strong analytic skills, especially in predictive modeling and data mining techniques