SENIOR ASSOCIATE

Location Designation: Hybrid – 3 days per week

Location: New York, NY

Offered Wage: $163,238/year

Duties: As part of the company’s Center for Data Science and Artificial Intelligence (CDSAi), leads and contributes to data analysis and modeling projects from project sample design, and business review meetings with internal and external clients. Determines requirements, deliverables, reception, and data processing. Performs data analyses and modeling to final reports and presentations, communicates results. 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. Creates high-performing predictive models and creative analyses leveraging advanced statistical and machine-learning techniques to address business objectives and client needs. Tests new statistical and machine-learning analysis methods and software and data sources for continual improvement of quantitative solutions. Implements analytical models into production by collaborating with internal Technology and Operations teams. Leverages data visualization tools for model testing, modeling results, and exhibiting data patterns. Designs performance metrics for model selection and performance monitoring. Performs data wrangling and data matching leveraging extract, transfer, load (ETL) techniques. Programs applications in multiple languages to explore a variety of data sources, gain data expertise, perform summary analyses, and prepare modeling datasets. Deploys analytical solutions in the Production systems. Communicates with internal stakeholders concerning product design, data specifications, and model implementations and with partners concerning collaboration ideas. Creates project milestone plans to ensure projects are completed on time and within budget. Follows industry trends in insurance and related data analytics processes and businesses. Participates in proof-of-concept tests for 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 Statistics, Computer Science, Mathematics, Machine-Learning or related quantitative field (willing to accept foreign education equivalent) plus three (3) years of experience coding and performing predictive modeling using large and complex datasets for the consumer finance or Insurance industry.

Or, alternatively:

Bachelor’s degree in Statistics, Computer Science, Mathematics, Machine-Learning or related quantitative field (willing to accept foreign education equivalent) and five (5) years of experience coding and performing predictive modeling using large and complex datasets for the consumer finance or Insurance industry.

Required Skills:

Experience must include 2 years in each of the following skills:

• Developing and deploying time-to-event survival models into production leveraging proportional hazard models, Random Survival Forest or accelerated failure time in the consumer finance or insurance industry;

• Programming production-ready code leveraging Python, R, SQL or Spark to extract and transform data from multiple data sources (using SQL, Oracle or Hadoop) for modeling data consistency management and data analysis reports; and to test, deploy, and integrate statistical models into business operation and decision-making processes;

• Developing parametric statistical models (including linear regression, time series, and generalized linear models (GLMs) and non-parametric models (including Random Forest, XGBoost, and gradient boosting machine (GBM) tree models) in R or Python using large and complex datasets for the insurance or consumer finance industry;

• Building and fine-tuning high-performing, robust statistical models for the consumer finance or insurance industry leveraging: regularization techniques (including Ridge, Lasso or elastic nets), variable selection techniques (including stepwise selections, weight of evidence, and information value), feature engineering (including transformation, binning, imputation, and high-level categorical reduction), validation (including holdouts, cross-validation, and bootstrapping), and proper model performance measures in R or Python; and,

• Performing complex data visualization leveraging R or Python for exploratory data analysis and model performance illustration to formulate business needs into statistical analysis and make model solution recommendations to business partners.

Eligible for Employee Referral Program.

This notice is being provided as a result of the filing of an application for permanent alien labor certification for the relevant job opportunity. Any person may provide documentary evidence bearing on the application to the Certifying Officer, U.S. Department of Labor, Employment and Training Administration, Office of Foreign Labor Certification, 200 Constitution Avenue NW, Room N-5311, Washington, DC 20210.

Overtime eligible: Exempt

Discretionary bonus eligible: No

Sales bonus eligible: No

Click here to learn more about our benefits. Starting salary is dependent upon several factors including previous work experience, specific industry experience, and/or skills required.

Recognized as one of Fortune’s World’s Most Admired Companies, New York Life is committed to improving local communities through a culture of employee giving and volunteerism, supported by the Foundation. We’re proud that due to our mutuality, we operate in the best interests of our policy owners. We invite you to bring your talents to New York Life, so we can continue to help families and businesses “Be Good At Life.” To learn more, please visit LinkedIn, our Newsroom and the Careers page of www.NewYorkLife.com.

Job Requisition ID: 90232