Marketing & Service Data Scientist - Vice President

Analysis, Artificial Intelligence, CASE, Data Analysis, Development, Foundation, GIS, Hadoop, HTTP, Management, Materials, Modeling, Networks, PowerPoint, Programming, Project, Python, Research, SAS, Sales, Security, Specification, SQL, Validation
Full Time
Work from home not available Travel required to 10%.

Job Description


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A career at New York Life offers many opportunities. To be part of a growing and successful business. To reach your full potential, whatever your specialty. Above all, to make a difference in the world by helping people achieve financial security. It-s a career journey you can be proud of, and you-ll find plenty of support along the way. Our development programs range from skill-building to management training, and we value our diverse and inclusive workplace where all voices can be heard. 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 service, supported by our Foundation . It all adds up to a rewarding career at a company where doing right by our customers is part of who we are, as a mutual company without outside shareholders. 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 www.NewYorkLife.com .

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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 predictive analytics and artificial intelligence solutions.


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In fact, we are building one of the first multivariate model-based continuous risk differentiations in the industry. 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, advertising allocation, new product development).


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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 drive the transformation of an industry. Is this not why we became data scientists?


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You will apply your highly developed technical predictive analytics skills to ingest and wrangle data, manage analytics projects and work on all aspects of marketing, service center and agency distribution analytics. In Service, examples are chat and voice call analytics, claims triaging and compliance analytics. In Marketing, we tackle everything from advertising spend optimization to customer acquisition and retention. In Agency distribution, example projects are triaging of agent candidates, geographic/GIS analytics to determine areas of opportunity (for sales, agent recruiting or general office locations), agent scoring (on performance and compliance).


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You will apply your leadership experience, high energy level and business sense to supervise staff, build relationships within the organizations of your internal customers, propose analytics strategy, create business cases, develop and evangelize succinct projects (define approach, create value proposition, gain stakeholder buy-in, define Tech implementation plan), drive several large initiatives, build and implement solutions at scale and give presentations as a subject matter expert.


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Responsibilities


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  1. Independently leads data analysis and predictive 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.
  2. Leads the group (team of 8 to start, growth from there) responsible for Marketing, Service and Agency analytics, including exploration/consolidation of a variety of internal and external data. Works closely with Marketing, Service, Agency, IT, Legal, Government relations and several other groups in designing, building and implementing predictive analytics and artificial intelligence solutions.
  3. Evangelizes the use of data-based decision making and Analytics within New York Life by active internal partnership management, discovering business opportunity and creating business value by executing on high-priority projects. (Future career growth will come from success here.)
  4. Utilizes advanced statistical techniques to create high-performing predictive models and creative analyses to address business objectives and client needs.-
  5. 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.
  6. Manages staff including goal setting, performance evaluation, effective resource allocation and career/skill development, hiring and training.
  7. Actively contributes to analytics strategy by contributing ideas, preparing presentation material for internal stakeholders, and product design/business case materials for NYL leadership.
  8. 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.
  9. Assures compliance with regulatory and privacy requirements during design and implementation of modeling and analysis projects.
  10. Travels to events and vendor meetings as needed ( < 10%).


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    Required qualifications


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  1. Predictive analytics related business development experience = building relationships and networks, conceptualizing and clearly defining projects, creating value propositions and business cases, getting buy-in from a variety of stakeholders and defining Tech implementation plan: Prior successes with creating and implementing value-adding predictive analytics/AI solutions strictly required.



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  • Demonstrated success in creating measurable business benefit for analytics while interacting with many stakeholders in a complex organization.
  • Ability to create business cases and socialize them to approval. Budget management experience.
  • 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.



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  1. Technical predictive modeling/AI and experimental design: Prior hands-on coding and predictive model building experience strictly required.



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  • Graduate-level degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics, or operations research.
  • 10+ years of experience with predictive analytics using large and complex datasets.
  • 5+ years of marketing analytics experience in large consumer facing business. Specific expertise in advertising allocation analytics, lead generation models, attrition and cross/up-sell, consumer segmentation, survey analytics, design/execution/analysis of multi-factor experiments.
  • Experience with distribution analytics, preferably with captive or independent sales force, including recruiting, evaluation, fraud/compliance, training issues.
  • Experience with service (call centers, chat, payment, claims, etc.) analytics and/or agent/advisor-based distribution analytics strongly preferred.
  • Health or life insurance experience is a plus.
  • Expertise in statistical modeling techniques such as linear regression, logistic regression, survival analysis, GLM, 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, bootstrap).
  • Substantial programming experience with several of the following: R, Python, (SAS - declining usage, soon phased out), SPARK, SQL, Hadoop. Exposure to GitHub.
  • Demonstrated expertise in statistical design of experiments.
  • Experience with data visualization (e.g. R Shiny, Spotfire, Tableau).


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  1. People management



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  • 5+ years of direct people management experience (performance reviews, hiring and firing authority, responsibility over project assignments) with teams of 5+ employees. 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.


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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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LI-TK1

EF-TK1

EOE M/F/D/V


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If you have difficulty using or interacting with any portions of this Web site due to incompatibility with an Assistive Technology, if you need the information in an alternative format, or if you have suggestions on how we can make this site more accessible, please contact us at: (212) 576-5811.

Date: Fri, 22 03 2019 00:00:00 GMT
Department: Data Analytics
Dice Id : 10127844a
Position Id : 80664-en_US
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