Director of Data Engineering and Data Science Technology

  • Competitive
  • New York, NY, USA
  • Permanent, Full time
  • New York Life Insurance Company
  • 18 Jan 18 2018-01-18

Director of Data Engineering and Data Science Technology

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.
Responsibilities

  1. Independently leads complex data projects from vendor/internal Tech database group engagement, security review, project design, business review meetings with internal and external clients deriving requirements/deliverables, reception and processing of data, to final reports/presentations, communication of results and implementation support.
  2. Leads a group responsible for comprehensive data support, computing platform support (liaison to tech) and external vendor management (technical and security aspects) for a world-class data science/advanced analytics organization.
  3. Plans and executes model implementations into various production systems (in collaboration with tech and business area).
  4. Has strong conceptual understanding of predictive modeling and deep understanding of data warehouses/hubs (including Oracle, Hadoop) and functions as liaison between the two.
  5. Evangelizes the use of data-based decision making and Analytics within New York Life by active internal partnership management and creating business value from high-priority projects.
  6. Proactively and effectively communicates in various verbal and written formats with internal stakeholders on product design, data specification, model implementations, with internal clients and stakeholders on project/test results, opportunities, questions. Resolves problems and removes obstacles to timely and high-quality project completion.
  7. Manages staff including goal setting, performance evaluation, effective resource allocation and career/skill development, hiring and training.
  8. Actively contributes to analytics strategy by contributing ideas, preparing presentation material for internal stakeholders, and product design/business case materials for NYL leadership.
  9. Follows industry trends in insurance and related data/analytics processes and businesses. Functions as the data expert in meetings with other internal areas and external vendors. Actively participates in proof of concept tests of new data, software and technologies.
  10. Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects.
  11. Travels to events and vendor meetings as needed (
    Required qualifications

  • Graduate-level degree with concentration in a quantitative discipline such as computer science, data science, economics, or operations research.
  • 7+ years of experience with consumer data projects using large and complex datasets. Experience with consumer insurance (life, health or P&C) is preferred.
  • 3+ years of direct people management experience. Proven ability to effectively manage own and associates' time while multitasking between multiple, time-sensitive projects and competing priorities in a dynamic business environment while maintaining strong, productive relationships with internal stakeholders and external partners. Ability to provide technical guidance to direct reports.
  • Specific experience with building/growing and retaining technical teams.
  • Strong verbal and written communications skills, listening and teamwork skills, and effective presentation skills. This is absolutely essential since you will have a lot of exposure to different internal groups (data, IT, actuarial, medical, underwriting, Legal, Agency, government relations, etc.) as well as third-party data partners.
  • Demonstrated experience in strategic and analytical leadership. Executive presence on high-level meetings. Credible conceptual understanding of predictive analytics.
  • Substantial programming experience with several of the following: SQL, SAS (STAT, macros, EM), R, Python, SPARK, other Hadoop languages. Exposure to Git.
  • Experience with data visualization (e.g. R Shiny, Spotfire, Tableau)
  • Proficiency in creating effective and visually appealing PowerPoint presentations.

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.

SF:LI-KR1
SF:EF-KR1
EOE M/F/D/V

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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.