Senior Data Scientist - Insurance Analytics - NJ #2812

Position Title Senior Data Scientist - Insurance Analytics - NJ #2812

Relocation Yes

Location Jersey City, NJ

Company is seeking a Senior Data Scientist for Insurance Analytics.

You will apply your highly developed analytical skills to work on all aspects of the insurance value chain, ranging from pricing models, fraud detection, process triaging, and financial risk models to a variety of other analytics solutions. You will also communicate with customers, external partners and internal departments, and hence will have the opportunity to get to know many carriers, vendors and data sources in the insurance industry.

Independently executes data analysis and modeling projects from project/sample design, reception and processing of data, performing analyses and modeling to final reports/presentations, communication of results and sales support.

Utilizes advanced statistical techniques to create high-performing predictive models and creative analyses to address business objectives and client needs.

Provides technical sales support, which may include various analyses and the preparation and presentation of analytical results.

Tests new statistical analysis methods, software and data sources for continual improvement of quantitative solutions.

Creates clear and easy to understand reports and/or PowerPoint decks for client meetings or third party collaborations.

Verbally presents analysis ideas, progress and results to internal managers, external partners and customers.

Communicates with internal groups on data specifications and with IT engineers on model/algorithm implementation.

Follows, and may create, detailed project plans to ensure projects are completed on time and within budget. Provides high quality ongoing customer/partner support; answering questions, resolving problems and building solutions.

Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects.

Shares knowledge within the analytics group.

Graduate-level degree with concentration in a quantitative discipline such as statistics computer science, mathematics, economics, or operations research.

Strong verbal and written communications skills, listening and teamwork skills, and effective presentation skills. This is absolutely essential since you will have a lot of exposure to different internal groups (data, IT, product and sales) as well as third-party partners and customers (insurance companies).

3+ years of relevant work experience including 1 year of statistical modeling and data mining in a P&C insurance content (insurance company or insurance consulting firm) using large and complex datasets. Experience with personal lines rating plan modeling is a strong plus. Life or health insurance experience is a bonus.

Expertise in statistical modeling techniques such as linear regression, logistic regression, GLM, tree models, cluster analysis, principal components, and feature creation, validation.

Programming experience with SAS (STAT, macros, EM), R and other statistical software (CART, Emblem, SPSS, Matlab). Greenplum and UNIX experience is a plus.

Detail-oriented technical aptitude with strong logical, problem solving, and decision-making skills. Excellent organization/planning skills and talent for managing many large and complex datasets.

Aptitude in performing multiple tasks and dealing with changing deadline requirements. This includes knowing when to escalate issues. Maintains a focused, flexible, organized, and proactive manner.

Proficiency in Microsoft Office (Excel, Word, PowerPoint).

Bottom line requirements we need notes on with candidate submittal:

1. Graduate degree with concentration in a quantitative discipline.

2. 3+ years of relevant work experience including 1 year of statistical modeling and data mining in a Property and Casualty insurance context (insurance company or insurance consulting firm).

3. Expertise in statistical modeling techniques such as linear regression, logistic regression, GLM, tree models, cluster analysis, principal components, and feature creation, validation.

4. Programming experience with SAS (STAT, macros, EM), R and other statistical software (CART, Emblem, SPSS, Matlab). Greenplum and UNIX experience is a plus.

All your information will be kept confidential according to EEO guidelines.