Jobs
From: Vicky Bell
Date: 05 Jun 2006
Subject: Novato, CA, USA: Data Mining Manager at Fireman's Fund
As a Data Mining Manager for Fireman's Fund 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.
Requirements:
- 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.
Contact:
Qualifed candidates, please email resumes to: bvklbell@comcast.net.
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