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Data Science Deliveries Design Leader - CVP

New York City, NY, USA | New York Life Insurance Company

  • Industry:
    Insurance - General
  • Position Type:
    Full-Time
  • Functions:
    General Management
    Biotech/R&D/Science
  • Experience:
    5-7 years
Job Description:
81 people have viewed this job

Leads the Delivery Design function within the Center for Data Science and Artificial Intelligence (CDSAi), reporting directly to the Chief Analytics Officer. The role has no direct reports at first, which could change as it develops.

Supports several large and high priority data science projects from a delivery design perspective.

Utilizes several standard and custom tools (that this person builds) to create interactive and captivating (digital) objects our internal stakeholders can use to understand our models and data science solutions.

Engages with internal stakeholders at multiple levels to uncover their business challenges, motivations and abilities.

Engages with the CDSAi team to learn about their technical solutions and skills.

Engages with the Tech team to gain knowledge about the various platforms and tools, and collaborates to deploy/create her/his own delivery solutions.

Works collaboratively with project and change managers within CDSAi and on other teams.

Supports internal events, expos, lunch & learns, etc. with displays and presentations.

Evangelizes the use of data-based decision making and Analytics within New York Life by active internal partnership management.

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. Contributes ideas and actively participates in proof of concept tests of new processes and technologies.

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


Business, creative and other non-technical

Demonstrated experience with building creative custom visualizations/digital objects for communicating data science to business stakeholders. We will want to see examples.

Deep understanding of the tools landscape for designing captivating data science deliveries.

Consulting experience is a plus.

Experience creating visual art pieces semi-professionally is a plus.

Health or life insurance experience is a plus.

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 (Agency, Service, data, IT, Legal, Marketing, government relations, etc.) as well as third-party data partners.

Demonstrated experience in strategic and analytical leadership. Executive presence on high-level meetings.

Proficiency in creating effective and visually appealing PowerPoint presentations.

Technical predictive modeling/AI, experimental design and visualization Hands-on coding and predictive model building experience required.

Graduate-level degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics, or operations research.

6+ years of experience with predictive analytics using large and complex datasets.

Demonstrated experience with data visualization and relevant tools (R Shiny, Bokeh, Tableau, etc.) Experience with developing custom tools beyond the standard packages.

Expertise in statistical modeling techniques such as linear regression, logistic regression, survival analysis, GLM, GBM, cluster analysis, principal components, feature creation, and validation.

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, bootstrap).

Substantial programming experience with several of the following R, Python, SPARK, SQL, Hadoop. Exposure to GitHub.

Demonstrated expertise in statistical design of experiments.


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