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The mission of Analytic Services is to make significant strategic and financial (top and bottom-line) contributions to Fireman�s Fund Insurance Company by enhancing decision-making throughout the Insurance process using rich and diverse data, deep customer information, and leading-edge analytical and predictive modeling techniques, tools, and expertise.

Housed within Customer Research & Strategies (CRS), Analytic Services comprises an entrepreneurial, project-oriented team that seeks to enhance Business decision-making in Marketing/Distribution (e.g., Target market identification, Lead identification and scoring, etc.), Underwriting (Cause-of-loss understanding, Risk qualification/assessment, Underwriting "sweet-spots", etc.), Claims (Subrogation identification, Fraud detection, etc.), and Business Operations (Audit candidate prediction, Coverage-gap prediction, Attrition prediction, etc). With core skills in data handling and data mining, the team has delivered key analyses to drive Corporate strategies and predictive models that have produced (and continue to produce) significant quantifiable financial returns. The team and department are highly regarded and very visible in the Company.

As a Sr. Data Mining Analyst you will play a critical role in leading, developing and managing high-impact analytical and predictive modeling initiatives in diverse Insurance-related areas. You will employ your end-to-end data mining skills, from data sourcing and transformations, to model building and model selection, to efficiently and effectively serve business needs and deliver successful outcomes for the business clients. You will report to the Sr. Director of Analytics, and will work closely with other members of CRS, including members of the Analytics team and the Market Research function. You will enjoy the benefits of project diversity, working on new and ongoing initiatives in diverse Insurance-related areas, and with your unique background, will have opportunities to make significant strategic and tactical contributions to all initiatives within the group. Besides working for a top-tier P&C Insurance carrier that has been in business for over 140 years, the position has the benefits of being located in beautiful Northern Bay Area (Marin county) and offers excellent career growth and development prospects.

Scope of Responsibilities:

• Apply background, knowledge, and skills in data handling and data mining to serve critical business uses in Statistical Analysis and Predictive Modeling.
• Serve as a key technical member in one or more projects such as � Fraud Detection, Subrogation Identification, Attrition/Retention Modeling, Customer Lifetime Value Modeling, Audit Prediction, Risk Qualification and Assessment, etc.
• Work with the project team to translate business needs to data elements in Data Warehouses (Claims and Customer) and other data Sources and creatively source, extract, match, and modify data to enable modeling efforts.
• Develop and apply insightful (maybe novel) data transformations and derivations to support downstream modeling initiatives.
• Employ appropriate sampling and dimensionality reduction techniques to handle data volume and size.
• Develop multiple models to address the business problem and validate results. Use model selection techniques (e.g., Lift/ROC curves) to identify the model to deploy.
• Communicate effectively with business stakeholders through the various stages of the project.
• Organize and present findings in a way that is understandable and useful to key stakeholders.
• Provide technical leadership and mentoring for other members in the team and play a key role in driving future direction and strategy of the group.
• Develop, foster, and enhance relationships with internal Business customers.

• Bachelor's degree in an Engineering or Science discipline with a strong quantitative focus is required. Advanced degree in Computer Science, Operations Research, Applied Statistics/Mathematics, or a quantitative field with a strong emphasis on Statistical Modeling and/or Machine Learning is strongly preferred. A Ph.D. is very desirable.
• Knowledge and work experience with one or more modeling techniques such as Decision/Regression Trees, Regression Analysis (e.g., GLMs), Neural Networks, Clustering/Segmentation Algorithms, Survival Analysis, etc. is required.
• Deep understanding of statistical and inductive biases of modeling algorithms and experience with dimensionality reduction and sampling techniques is required.
• Experience with Unstructured Data Analysis and Text Mining is a plus.
• Experience with statistical software (SAS, SPSS, Splus, R, etc.) is required. SAS programming experience is preferred, with SAS Enterprise Miner experience being highly desirable.
• SQL skills are required and knowledge of databases/DBMS is desirable.
• Knowledge and/or experience in Insurance -- Marketing, Underwriting, Claims, or Actuarial is strongly preferred.
• 5+ years of relevant work experience is preferred, although exceptions can be made for strong candidates.
• Strong verbal, written, and presentation skills are required.
• Must be self-motivated, action-oriented and capable of working both independently and as part of a team.
• Demonstrated leadership ability/potential will be highly valued.

For more information on Fireman's Fund, please visit our website at www.firemansfund.com.