Director of Data Engineering and Data Science Technology
New York Life, the largest writer of retail life insurance in the U.S. and a top player in annuities, long-term care and mutual funds, is seeking a Director of Data Engineering and Data Science Technology in its Center for Data Science and Analytics.
The company has over 150 years of history and while usable data does not quite go back this far, we have a wealth of internal information on consumers, policies and their performance, as well as applicants, prospects and our 12,000 agents. We also have a multitude of external data from a great variety of sources. New York Life is likely the most data-rich company in the life insurance industry. Analytical challenges range from mortality risk (with a number of both medical and non-medical components) to agent recruiting decisions, consumer analytics (segmentation, response, conversion, retention, up-sell), fraud detection and digital advertising placement.
The Center for Data Science and Analytics is the innovative corporate Analytics group within New York Life. We are a rapidly growing entrepreneurial department which aims to design, create and offer innovative data-driven solutions for many parts of the enterprise. We are aided by New York Life’s existing business with a large market share in individual life insurance. We have the freedom to explore external data sources and new statistical techniques, and are excited about delivering a whole new generation of Analytical solutions.
In fact, we are building one of the first multivariate model-based continuous risk differentiations in the industry. This model will incorporate current underwriting best practices (including medical rules) as features and add other data sources, patterns/ideas and variables to essentially create a rating plan to support the next generation underwriting process at New York Life. We are also working on models for differentiated advertising allocation by geography, channel and segment. Geographic analytics on agents and customers, application fraud detection, agent success prediction and client prospecting analytics (off-line and on-line) are other exciting examples of enormous incremental value from analytics. Our products will be implemented into real-time core business processes and decisions that drive the company (e.g. underwriting, pricing, agent recruiting, prospecting, new product development).
We work with data ranging from demographics, credit and geo data to detailed medical data (medical test results, diagnosis, prescriptions) and social media information. We have a modern computing environment with a solid suite of data science/modeling tools and packages, and a large (but manageable) group of well-trained professionals at various levels to support you. Life insurance is on the verge of huge change. This is a chance to be part of, actually to drive, the transformation of an industry. Is this not why we became data scientists?
You will apply your highly developed data and process skills to create model-ready data (from internal and external sources) for several teams of predictive modelers, and function as the liaison from the Data Science team towards the Technology organization regarding data, computing platform and model implementation.
You will apply your leadership experience, high energy level and business sense to supervise staff, communicate with internal stakeholders and external vendors while effectively leading large and complex data projects.
Location: Manhattan (midtown, walking distance from Penn Station and Grand Central). Relocation assistance is available for remote applicants but work from other locations is not possible long term.
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*Based on revenue as reported by “Fortune 500, ranked within Industries, Insurance: Life, Health (Mutual),” Fortune Magazine, June 17, 2016. See http://fortune.com/fortune500/ for methodology.
**Total surplus, which includes the Asset Valuation Reserve, is one of the key indicators of the company’s long-term financial strength and stability and is presented on a consolidated basis of the company.
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.