Corporate Vice President - Lead Data Scientist, Strategic Business Analytics

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Posting Date: Jun 20, 2024

Location: Remote, NY, US

Company: New York Life Insurance Co

Location Designation: Hybrid - 1 day per quarter 

 

 

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 AI and Data team.

 

The company has 179 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 vast 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.

 

When you join New York Life, you are 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 will 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’s AI and Data team delivers innovative data, insights, and AI solutions for the organization. Our AI team works on a diverse portfolio of AI and GenAI projects, by combining agile and entrepreneurial drive with industry-leading methods and tools. Our efforts are fully supported by executive leadership, and we work hand in hand with our Business Partners through all stages of model development from ideation to deployment. As it takes multiple skill sets to deliver AI models to production, our AI team includes product managers, data scientists, MLOps engineers, program managers, a model validation & governance group, and a communications & development group.

 

The Artificial Intelligence and Data (AI & D) Team is the innovative corporate data and analytics group within New York Life. We are a rapidly growing entrepreneurial department charged with the design and creation of innovative data-driven solutions for many parts of the enterprise. We have the freedom to explore external data sources and new techniques and are delivering exciting next generation solutions.

The Lead Data Scientist reports to AI lead of Field Productivity and Field Operations Value Streams. A good understanding of predictive analytics (including the process of building and deploying models) and technology is essential. Examples of Field and Agency sales Data Science products that have built and are currently working on are below.

Candidate Assessment Tool

Agent sales and retention forecasting models

Gen AI tools for Agents

 

Responsibilities

  • Independently 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 and machine learning techniques to create high-performing predictive models and creative analyses to address business objectives and client needs. Tests new statistical and machine learning analysis methods, software, and data sources for continual improvement of quantitative solutions.
  • Implements analytical models into production by collaborating with technology and operation teams. Utilizes proper data visualization tools for model testing, modeling results and data patterns exhibition. Design performance metrics for model selection and performance monitoring.
  • Utilizes data wrangling/data matching/ETL techniques while programming in several languages to explore a variety of data sources, gain data expertise, perform summary analyses and prepare modeling datasets. Deploys analytical solution in production systems.
  • 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.
  • Creates project milestone plans to ensure projects are completed on time and within budget. Provides high quality ongoing customer support (e.g., answering questions, resolving problems, and building solutions).
  • 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.           

  • Master’s degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics or operations research and 5 years of relevant industry experience OR Ph.D. with concentration in similar fields and 2-3 years of relevant industry experience OR Associateship/Fellowship in one of the Actuarial Societies and 5 years of data science experience.
  • 2+ years of hands-on experience in coding and predictive modeling using large and complex datasets in a business setting. Working knowledge of GitHub.
  • Demonstrated capability to develop and deploy data science solutions and create values with limited guidance.
  • Strong verbal and written communications skills, listening and teamwork skills, and effective presentation skills. This is 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 in higher-level meetings. Credible functional expertise in predictive analytics.
  • Substantial programming experience with Python, R, SQL, and Spark. Experience with data wrangling, data matching, and ETL techniques while programming in several languages (Python, R, SQL, and Spark) to extract and transform data from a variety of data sources (Oracle, SQL, Hadoop).
  • Strong expertise in statistical modeling and machine learning techniques such as linear regression, logistic regression, and other Generalized Linear Models (GLMs), survival analysis, tree models (Random Forest, GBM, XGBoost), cluster analysis, principal components. 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). Experience with data visualization (e.g., R Shiny, Tableau, Spotfire).
  • Deep statistical knowledge is a plus.
  • Experience with insurance or consumer financial data is a plus.
  • Experience using open-source tools and libraries for Natural Language Processing, entity recognition, topic identification, and Regular Expression is a plus.

Location

  • Manhattan (NoMaD, walking distance from Penn Station, Grand Central Station, Union Square).
  • Relocation is available.
  • On-site as needed (currently 3 days every other month)

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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 www.NewYorkLife.com.

Job Requisition ID: 90370

 

 

 


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