Jobs

At Fireman's Fund, you're building a challenging career at the same time as bringing a sense of stability to people's lives. You're also contributing to our success and our reputation as a leader in the field with your skills and expertise. For this you are appreciated, acknowledged, and rewarded. We believe that if you hold on to great people, everyone wins. Just more proof that a career with Fireman's Fund isn't just a good idea. It's a smart move.

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 performing statistical analysis and/or predictive modeling in one or more initiatives
• 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 analysis/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

Greg Wright, GWright@ffic.com

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An equal opportunity employer.