CVP, Director of Data Science, Marketing Sales and Geospatial Analytics

Full Time


    DirectorSalesArtificial IntelligenceAnalyticalPythonITGISNLPSQLDomino

    Job Description

    Location Designation: Hybrid

    When you join New York Life, you're joining a company that values career development, collaboration, innovation, and inclusiveness. We want employees to feel proud about being part of a company that is committed to doing the right thing. You'll have the opportunity to grow your career while developing personally and professionally through various resources and programs. New York Life is a relationship-based company and appreciates how both virtual and in-person interactions support our culture.

    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 Lead Data Scientist in its Center for Data Science and Artificial Intelligence (CDSAi).

    The company has 177 years of history and while usable data does not quite go back that 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. Analytical challenges range from mortality risk to agent recruiting decisions, service optimization, consumer analytics (segmentation, response, conversion, retention, up-sell), fraud detection, advertising allocation and office footprint optimization.

    The Center for Data Science and Artificial Intelligence (CDSAi) is the 60-person innovative corporate Analytics group within New York Life, led by Chief Analytics Officer Glenn Hofmann ( ). We are a rapidly growing entrepreneurial department which designs, creates, and offers innovative data-driven solutions for many parts of the enterprise. For more information on CDSAi, please visit our website ( ).

    In the 6 years of the existence of CDSAi we have built a lot of predictive modeling solutions that are being used by various areas in the company. We have also stood up a modern model deployment platform that allows our models to be accessed in real time or batch (via APIs) from any production system in the company.

    We are currently expanding our team of data scientist who work on Service data science products. The role reports to Marina Printz ( ), who currently leads the Marketing and Sales Data Science team. A good understanding of predictive analytics (including the process of building and deploying models) and technology is essential.

    Examples of Data Science products that have built and are currently working on are below.
    • Next Best Action
    • Customer Cross-Sell models
    • Fraud Alerts

    • Leads and contributes to data analysis and modeling projects from project/sample design, business review meetings with internal and external clients deriving requirements/deliverables, reception, and processing of data, performing analyses and modeling to final reports/presentations, communication of results and implementation support.
    • Demonstrates to internal and external stakeholders how analytics can be implemented to maximize business benefits.
    • Provides technical support, which includes strategic consulting, needs assessments, project scoping and the preparation/presentation of analytical proposals.
    • Utilizes advanced statistical techniques to create high-performing predictive models using R or Python, and creative analyses to address business objectives and client needs.
    • Tests new statistical analysis methods, software and data sources for continual improvement of quantitative solutions.
    • Proactively and effectively communicates in various verbal and written formats with internal stakeholders on product design, data specification, model implementations, with partners on collaboration ideas and specifics, with clients and account teams on project/test results, opportunities, questions.
    • Resolves problems and removes obstacles to timely and high-quality project completion.
    • Create project milestone plans to ensure projects are completed on time and within budget.
    • Provides high quality ongoing customer support, answering questions, resolving problems and building solutions.
    • Validate ongoing data science projects, including coding scripts and summary results for data manipulation/cleaning and modeling.
    • Challenge existing method adopted in the project with alternatives. Provide feedback to improve the deliverables.
    • Teach and explain basic data science concepts and tools to general internal audience.
    • Follows industry trends in insurance and related data/analytics processes and businesses.
    • Functions as the analytics expert in meetings with other internal areas and external vendors.
    • Actively participates in proof-of-concept tests of new data, software and technologies.
    • Shares knowledge within Analytics group.
    • Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects.
    • Travels to events and vendor meetings as needed (<10>

    Required qualifications
    • Graduate-level degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics, physics, or operations research
    • 5+ years of experience with predictive analytics in financial services or insurance (preferred but not mandatory) using large and complex datasets.
    • 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, Service, Agency, government relations, etc.) as well as third-party data partners.
    • Demonstrated experience in strategic and analytical leadership. Executive presence on higher -level meetings. Credible functional expertise in predictive analytics.
    • Strong expertise in statistical modeling techniques such as linear regression, logistic regression, survival analysis, GLM, tree models (Random Forests and GBM), cluster analysis, principal components, feature creation, and validation.
    • Strong expertise in regularization techniques (Ridge, Lasso, elastic nets), variable selection techniques, feature creation (transformation, binning, high level categorical reduction, etc.) and validation ( hold-outs , CV, bootstrapping ).
    • Experience in geo-analytics and geospatial data science, both using commercial GIS and open source.
    • Experience with NLP and language models.
    • Substantial programming experience with several of the following: R, Python, PySpark , SQL, Hadoop. Exposure to GitHub, Domino Data Labs.
    • Experience with data visualization (e.g., R Shiny, Tableau)
    • Experience with third-party consumer data (Acxiom, Claritas , etc.) is a plus.
    • Proficiency in creating effective and visually appealing PowerPoint presentations.


    Salary range: $117,500-$177,500

    Overtime eligible: Exempt

    Discretionary bonus eligible: Yes

    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 .

    Job Requisition ID: 87682