Employer: New York Life Insurance CompanyJob Title: Corporate Vice President, Lead Data ScientistLocation: This position reports to the NY Life Headquarters in New York, NY but applicants may work from a Home Office anywhere in the United StatesOffered Wage: $178,200.10/yearDuties: As part of the company's Center for Data Science and Artificial Intelligence (CDSAi) corporate analytics group, applies analytical skills to work on all aspects of the life insurance value chain, ranging from risk models, fraud detection, customer behavior study, process triaging, and marketing prediction to a variety of other analytics solutions. Applies technical data, analytical, and programming skills to ingest, wrangle, and explore external and internal data to create data assets and reports. Functions as the data expert and prepares data for modeling, supports production deployment of models, and builds world-class machine-learning models to solve tangible business problems. Contributes to data analysis and modeling projects from project and sample design, business review meetings with internal and external clients to determine requirements and deliverables, and the receipt and processing of data. Performs analyses and modeling for final reports and presentations, communicates results, implements support, and 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. Leverages advanced statistical and machine-learning techniques to create high-performing predictive models and creative analyses to address business objectives and client needs. Tests new statistical and machine-learning analysis methods, software, and data sources for continual improvement of quantitative solutions. Implements analytical models into production by collaborating with internal Technology and Operation teams.Minimum Education & Experience Requirements:Master's degree in Statistics, Computer Science, Mathematics or Machine-Learning (or equivalent foreign education) and four (4) years of experience performing data analytics and statistical modeling using complex large-sized datasets in the consumer finance domain.Or, in the alternative:Bachelor's degree in Statistics, Computer Science, Mathematics or Machine-Learning (or equivalent foreign education) and six (6) years of experience performing data analytics and statistical modeling using complex large-sized datasets in the consumer finance domain.Required Skills:Experience must include 4 years in each of the following skills:(1) Developing statistical models to improve business outcomes and increase revenues using generalized additive model (GAM), generalized linear model (GLM), time series forecasting model, gradient boosting model (GBM), neural network, and natural language processing (NLP) to build the model using Ridge, Lasso, elastic nets regularization; using t-distributed stochastic neighbor embedding (t-SNE) and independent component analysis (ICA) to reduce dimensionality; using label encoding, scaling and tokenization feature engineering techniques; using holdout and cross-validation to perform model validation; and using precision-recall curves, Gini, and lift and gain charts to measure model performance;(2) Automating analysis processes and managing large-scale data leveraging Spark and Hadoop to ensure efficiency, scalability, and cost-effectiveness; coding in Python, R, and SQL for data processing; and, leveraging Tableau and Spotfire to visualize analysis processes;(3) Deploying real-time models into production environments, including writing production-ready code leveraging Visual Studio Code, conducting rigorous unit testing and stress testing leveraging PyTest, and integrating models into existing business processes leveraging R, Python, and SQL code to ensure accuracy, reliability, and compliance with regulations;(4) Collaborating with cross-functional teams comprised of Product Managers, Engineers, and business leaders to design and implement Underwriting project proposals to measure the impact of business objective changes achieved by communicating complex data analysis results leveraging Plotly and Tableau visualization tools and summarizing insights in a narrative format through PowerPoint presentations; and,(5) Mentoring junior Data Scientists and coaching them to navigate complex data science problems, machine-learning algorithms and statistical analysis, using R, Python and SQL, ensuring the application of sound methodologies and adherence to project timelines, and conducting thorough code reviews, including version control with Git to enforce coding practices and standards.Submit resume to NYLJobs06@newyorklife.com

Minimum Salary: 178200.10 Maximum Salary: 178200.10 Salary Unit: Yearly