Experience Inc. Jobs

Employer: New York Life Insurance CompanyJob Title: Corporate Vice President, Lead Data ScientistLocation: This position is fully remote reporting to New York Life headquarters in New York, NY. Applicants may work from a Home Office anywhere in the United States.Offered Wage: $178,938/yearDuties: Leads data analysis and modeling projects from project and sample design. Participates in business review meetings with internal and external clients to develop and determine requirements and deliverables. Performs data analyses and modeling to final reports and presentations, communicates results, and provides implementation support. Demonstrates to internal and external stakeholders how analytics can be implemented to maximize business benefits. Provides technical support, including strategic consulting, needs assessments, project scoping, and preparing and presenting analytical proposals. 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 data science solutions to address business objectives and client needs. Tests new statistical and machine learning methods, software, and data sources for continual improvement of quantitative solutions. Leverages data wrangling and extract, transform, and load (ETL) techniques and programs applications in several languages to explore a variety of data sources, gain data expertise, perform summary analyses, and prepare modeling datasets. Implements analytical models into production by collaborating with internal Technology and Machine-Learning Operations teams. Leverages data visualization tools for model testing, modeling results, and data pattern exhibition. Designs performance metrics for methodology selection and performance monitoring. Leverages scientific approaches (experimental design) to verify the performance of algorithms and predictive models. Works closely with internal IT, Legal, and Government Relations business units to design, build, and implement data science solutions. Communicates with internal stakeholders concerning product design, data specifications, and model implementations; with internal partners concerning collaboration ideas; and, with internal clients and stakeholders concerning project and test results, opportunities, and inquiries. Resolves problems and removes obstacles to timely and high-quality project completion. Follows industry trends in insurance and related data and Artificial Intelligence (AI) processes. Functions as the analytics expert in meetings with other internal business partners and external vendors. Contributes ideas and participates in proof of concept (PoC) tests of new processes and technologies. Ensures compliance with regulatory and privacy requirements during the design and implementation of modeling and data science projects.Education & Experience Requirements:Master's degree in Statistics, Data Science, Actuarial Science, Computer Science, Mathematics or a related quantitative discipline (willing to accept foreign education equivalent) plus three (3) years of experience performing statistical and predictive modeling using large and complex datasets for insurance or finance industry applications.Or, alternatively:Bachelor's degree in Statistics, Data Science, Actuarial Science, Computer Science, Mathematics or a related quantitative discipline (willing to accept foreign education equivalent) and five (5) years of experience performing statistical and predictive modeling using large and complex datasets for insurance or finance industry applications.Required Skills:Experience must include 2 years in each of the following skills:(1) Developing statistical and machine-learning models for insurance industry applications leveraging Cox regression survival analysis, generalized additive modeling (GAM), and XGBoost and topic modeling to improve business outcomes and increase business value; (2) Developing productionized data science solutions in the following programming languages: R, Python, and SQL; managing large-scale data using Spark; building dashboards and user interfaces (UI) leveraging R Shiny and Dash; performing code management and version control using Git to ensure the delivered solutions are accurate and reliable and can be seamlessly integrated into existing business process; (3) Developing assumption models using seriatim-level life insurance experience data to support financial models and practices for pricing, reserving, asset and liability management, and capital management; (4) Building and deploying robust real-time or batch models into production environments so deployed models comply with regulations and auditing requirements and are able to generate actionable business strategies and improve operational efficiency applying the following: selection techniques and regularization techniques (Ridge, Lasso, and elastic nets), feature engineering techniques for structured and unstructured data (transformation, binning, text standardization, and cleaning), leveraging model validation (hold-outs and cross-validation), and model performance assessment techniques (Actual and Expected ratio, precision-recall curves, and lift); and, (5) Collaborating with cross-functional teams, including Actuarial, Finance, and Service stakeholders, Product Managers, and Engineers to identify business objectives and analyze business value, translate them into data science solutions and communicate and present complex quantitative analytical results to both technical and non-technical stakeholders.Submit resume to NYLJobs04@newyorklife.com

Minimum Salary: 178938 Maximum Salary: 178938 Salary Unit: Yearly