Corporate Vice President, Lead Data Scientist

at  New York Life Insurance Co

Job Requisition ID: 90094
Location Designation: Fully Remote
Location: New York, NY This position reports to the NY Life headquarters in New York, NY. Applicants may work from a Home Office anywhere in the U.S.
Offered Wage: $182,499.98/year
Duties: Leads data analysis and modeling projects from project and sample design. Participates in business review meetings with internal and external clients to develop requirements and deliverables. Performs analyses and modeling to final reports and presentations, communicates results, and provides implementation support. Demonstrates to stakeholders how analytics can be implemented to maximize business benefits. Provides strategic consulting, assessments, and project scoping and prepares and presents analytical perspective. Drives the use of data-based decision-making and analytics by active internal partnership management, discovering business opportunities, and creating business value by executing high-priority projects. Leverages advanced statistical and machine-learning techniques to create high-performing predictive models and creative analyses to address business objectives and client needs. Leverages scientific approaches (experimental design) to verify the performance of algorithms and predictive models. Works closely with business and technology partners to design, build, and implement Artificial Intelligence (AI) and data science solutions. Communicates with internal stakeholders concerning product design, data specifications, and model implementations. Collaborates with partners concerning ideas and specifics, and with internal clients and stakeholders concerning projects, test results, opportunities, and questions. Resolves problems and removes obstacles to ensure timely and high-quality project completion. Follows industry trends related to insurance and related data and AI processes and businesses. Participates in proof-of-concept tests of new data, software, and technologies. Ensures compliance with regulatory and privacy requirements during the design and implementation of modeling and analysis projects.

EDUCATION & EXPERIENCE REQUIREMENTS:

Master’s degree in Mathematics, Statistics, Data Science, Computer Science, Economics, Operations Research or related quantitative field (willing to accept foreign education equivalent) plus three (3) years of experience as a Data Scientist or performing predictive analytics within the financial services or insurance industry.
Or, alternatively:
Bachelor’s degree in Mathematics, Statistics, Data Science, Computer Science, Economics, Operations Research or related quantitative field (willing to accept foreign education equivalent) plus five (5) years of experience as a Data Scientist or performing predictive analytics within the financial services or insurance industry.

REQUIRED SKILLS:

Experience must include 2 years in each of the following skills:
(1) Performing statistical modeling leveraging linear regression, generalized linear modeling (GLM), survival analysis, XgBoost, neural network, and deep learning machine-learning models, cluster analysis, and unsupervised learning approaches;
(2) Performing regularization leveraging Ridge, Lasso, and elastic nets regularization techniques and performing predictive modeling leveraging variable selection techniques;
(3) Performing transformation, binning, and high-level categorical reduction feature creation; and hold-outs, cross-validation, and bootstrapping validation; and,
(4) Programming applications leveraging 2 or more of the following languages: R, Python, PySpark, SQL or Hadoop.

Please refer the Job description for details