Opportunity for a creative predictive modeler/data scientist to use machine learning, statistics, data mining, and analytic skills to influence the decision making.
Company: Allstate Insurance
Location: Northbrook, IL
Web: www.allstate.com
This is an opportunity for a creative predictive modeler/data scientist to use your machine learning, statistics, data mining, and analytic skills to influence the decision making of a Fortune 100 company. The Rating Plan Development team (RPD) is responsible for identifying and developing pricing opportunities that will enable Allstate to generate profitable market-share growth.
RPD currently has multiple openings, from entry-level to experienced predictive modelers. Key Responsibilities and Knowledge/Skills listed below span the entire predictive modeling career track, and candidates will be considered for the position that best matches their skills and experience.
AREA OF RESPONSIBILITY:
In alignment with corporate goals, specific responsibilities for the Predictive Modeler/Data Scientist will include:
- Creating and/or contributing to best-in-class predictive models taking into account business constraints.
- Helping to shape best practices around application of statistical modeling.
- Leading and/or implementing projects that yield actionable insights the business can use to increase customer satisfaction, policy growth, retention, and loss experience
PROFESSIONAL BACKGROUND:
The successful candidate will have a minimum of 3 to 5 years of experience in a predictive modeling / data scientist role in the insurance industry or 4 to 7 years relevant experience outside of insurance.
The candidate must of demonstrated increasing levels of responsibility in:
- Proven ability to build predictive models.
- Solid skills and training in machine learning, statistical modeling, data mining or related field.
- Excellent computer skills, including strong programming skills in any language.
- Experience using machine learning algorithms (for example: Generalized Linear Models, Boosting, Decision Trees, Neural Networks, SVM, Bayesian Methods, Ensemble techniques, etc.)
- Ability to concentrate on loosely defined problems which require application of creative approaches.
- Ability to transfer knowledge to a variety of audiences.
- Understanding of algorithmic complexity and scaling of run time and memory usage with larger datasets
- Solid knowledge of linear algebra and convex optimization techniques.
- Experience tackling large data sets or familiarity with tools such as Hadoop or MapReduce.
EDUCATIONAL BACKGROUND:
A graduate degree strongly preferred; Actuarial designation (ACAS/FCAS) a plus but not required. Major preference(s) include Machine Learning, Statistics/Applied Statistics, Computer Science, or related field.
_Contact_:
Interested and qualified applicants must
apply online via Allstate jobs
Requisition: 000D7D
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