Principal Predictive Modeler/Data Scientist - Insurance Analytics - NJ #2811

Right Talent Right Now; Jersey City (NJ); On-site; USD 100,000 - 140,000; Full time

Job summary

A leading analytics firm is seeking a Principal Predictive Modeler/Data Scientist. This senior-level role in Jersey City, NJ, focuses on developing innovative data-driven products for the property, casualty, and life insurance sectors. Candidates must have extensive statistical modeling experience and strong communication skills, with at least 8 years of relevant work, including proficiency in statistical software like SAS and R. The position involves leading complex analytics projects and ensuring compliance with regulatory standards.

Qualifications

• Graduate-level degree with concentration in a quantitative discipline like statistics, computer science, or economics.
• 8+ years of relevant work experience including 3 years of statistical modeling and data mining in a P&C insurance context.
• Expertise in statistical modeling techniques like linear regression, logistic regression, and GLM.

Responsibilities

• Apply analytical skills to the insurance value chain and develop pricing models.
• Communicate with customers and lead complex analytics projects.
• Execute data analysis and modeling projects from design to final reports.

Skills

Statistical modeling

Data mining

Verbal communication

Written communication

Teamwork

Education

Graduate degree in quantitative discipline

Bachelor's degree with CAS Associate or Fellow status

Tools

SAS

R

Microsoft Office

SPSS

Matlab

Job description

Principal Predictive Modeler/Data Scientist - Insurance Analytics - NJ #2811

• Full-time

Position Title Principal Predictive Modeler/Data Scientist - Insurance Analytics - NJ #2811

Relocation Yes

Location Jersey City, NJ

Company is seeking a Principal Predictive Modeler / Data Scientist. This is a senior-level technical position.

Rapidly growing unit aims to design, create and offer innovative data-driven products to the property and casualty insurance as well as life insurance and parts of the credit industry.

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 while effectively leading complex analytics projects.

Independently executes data analysis and modeling projects from project/sample design, business review meetings with internal and external clients deriving requirements/deliverables, 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.

Demonstrates to internal and external customers how analysis can be implemented to maximize business strategies including cost benefit analyses. Provides technical sales support, which may include providing strategic consulting, needs assessments and the preparation and presentation of analytical proposals.

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.

Provides high quality ongoing customer and sales support; uncovering opportunities, 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.

Required qualifications:

Graduate-level degree with concentration in a quantitative discipline such as statistics computer science, mathematics, economics, or operations research OR Bachelor's degree with CAS Associate or Fellow status or substantial exam progress.

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).

8+ years of relevant work experience including 3 years of statistical modeling and data mining in a P&C insurance context (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.

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

Proficiency in Microsoft Office (Excel, Word, PowerPoint). Not just software use but proficiency in creating effective and visually appealing PowerPoint presentations, and well-structured error-free and readable spreadsheets.

Bottom line requirements we need notes on with candidate submittal:

1. Graduate degree with concentration in a quantitative discipline or Bachelor's degree with CAS Associate or Fellow status.
2. 8+ years of relevant work experience including 3 years 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.