Statistician/Data Scientist
New York , New York
September 10, 2016

New York Life Insurance Company (“New York Life” or “the company”) is the largest mutual life insurance company in the United States*. Founded in 1845, New York Life is headquartered in New York City, maintains offices in all fifty states, and owns Seguros Monterey New York Life in Mexico.


New York Life is one of the most financially strong and highly capitalized insurers in the business. The company reported 2015 operating earnings of $1.875 billion. Total assets under management at year end 2015, with affiliates, totaled $528 billion. New York Life holds the highest possible financial strength ratings currently awarded to any life insurer from all four of the major ratings agencies: A.M. Best, A++; Fitch AAA; Moody’s Aaa; Standard & Poor’s AA+. (Source: Individual Third Party Ratings Report as of 8/11/15).


Financial strength, integrity and humanity—the values upon which New York Life was founded—have guided the company’s decisions and actions for over 170 years.




Statistician / Data Scientist


New York Life’s Center for Data Science and Analytics is responsible for delivering high impact analytic solutions to address business problems aligned with our strategic initiatives.  We cover a vast spectrum of the business including Underwriting, Consumer Research, Digital Marketing, Sales and Fraud.  We are looking for Data Scientists / Statisticians / Data Engineers at various levels of seniority to join the team.


Ideal candidate components

  • High fluency in a language such as R, Python or SAS.  Expertise or high interest in learning in big data technologies


  • Solid foundation in standard modern statistical techniques such as different types of Regression, Experimental Design, Survival Analysis, Random Forests, SVMs, Cluster Analysis, MC Simulation,  …


  • Proficient presentation skills and comfort presenting to audiences with vastly differing degrees of analytical expertise


  • Prior work experience with variety of different data – structured / unstructured, rare events, varying sizes of datasets


  • Demonstrated ease of working on complex analytical problems.  Forward thinking and proactively seeks to improve processes or prevent road blocks


  • Strong engagement in all aspects of designing a custom analytic solution in collaboration with our business partners from idea generation, selection of analytic approach to the solution development and deployment as well as performance evaluation and testing


  • Understanding of all aspects of model building from data collection, stratified sampling, feature engineering, variable selection, test and validation to presenting results to both internal and external teams

Experience and Background


  • We prefer to hire individuals who have an advanced degree (MS or PhD) in a field such as Statistics, Biostatistics, Bioinformatics, Applied Mathematics, Economics or another field which is highly analytical / quantitative.


  • Prior work experience from financial institutions, insurance, marketing or health care would be beneficial, but pertinent skills can be obtained from any industry





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*Based on revenue as reported by “Fortune 500, Ranked within Industries, Insurance: Life, Health (Mutual),” Fortune Magazine, June 15, 2015.  See  for methodology.

1. Operating earnings is the key measure use by management to track Company’s profitability from ongoing operations and underlying profitability of the business. This indicator is based on generally accepted accounting principles in the US(GAAP), with certain adjustments Company believes to be appropriate as a measurement approach ( non GAAP), primarily the removal of gains or losses on investments and related adjustments.

2. Assets under management represent Consolidated Domestic and International insurance Company Statutory assets (cash and invested assets and separate account assets) and third party assets principally managed by New York Life Investment management Holdings LLC, a wholly owned subsidiary of New York Life Insurance Company.

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