Senior Data Scientist

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Date: Oct 11, 2021

Location: New York, NY, US

Company: New York Life Insurance Co

 

When you join New York Life, you’re joining a company that values development, career growth, collaboration, innovation, and diversity & inclusion. We want employees to feel proud about being part of a company that is committed to doing the right thing. Through various resources and programs, you can grow your career while developing personally and professionally.

 

 

 

The Center for Data Science and Artificial Intelligence (CDSAi) is the innovative corporate data science group within New York Life. With over 40 team-members, consisting of data scientists, data engineers and project managers, we design and create unique data-driven solutions for the foundational arm of the enterprise. We have the freedom to explore external data sources and new machine learning techniques. Since the team’s inception in 2016, we have been delivering a whole new generation of model-driven solutions. Our resulting data science products are implemented into real-time business processes and decisions that drive the company.

 

At the end of 2020, New York Life completed the acquisition of Cigna’s group life, accident and disability insurance business. This was the largest acquisition in New York Life’s history, adding roughly three thousand employees and more than nine million customers. With this expansion, CDSAi has identified a number of focus areas that would benefit from data science support: claims management (e.g. claims segmentation, claim manager profiling, claim eligibility automation), distribution (e.g. territory/opportunity analytics, sales forecasting), and underwriting (e.g. triage modeling, risk prediction modeling). There are many other areas within our strategic businesses which could gain enormous incremental value from our expertise providing us with a wide variety of exciting data science solutions to develop.

 

We have a state-of-the-art computing environment with a solid suite of machine learning tools and packages, a model deployment platform, and a large group of well-trained professionals at various levels to support you. Life insurance has already started undergoing a huge change. This is a chance to be part of and actually to drive, the continued transformation of an industry. Is this not why we became data scientists?

 

You will engage in all aspects of the model development lifecycle including model design, development, interaction with business partners, testing, validation and implementation.

 

You will apply your highly developed analytical skills to work on all aspects of the life insurance value chain, ranging from risk models, process triaging, and marketing predictions to a variety of other analytics solutions.

 

You will apply your technical data/ETL/programming skills to ingest, wrangle and explore external and internal data to create reports, function as the data expert and prepare data for modeling and support production deployment of models OR apply your technical modeling skills to build world-class predictive models for solving tangible business problems.

 

You will apply your high energy level and business sense to communicate with internal stakeholders and external vendors while effectively contributing to complex data science projects.

 

There are numerous opportunities to grow within the team. CDSAi supports continued training in data science (e.g. online course, conferences) and other areas such as leadership and communication (e.g. improving presentation skills, developing executive presence). Every summer, CDSAi hires graduate students to intern for the data scientists, benefiting both the interns (who gain valuable professional experience) and the data scientists (who gain valuable management experience). CDSAi managers actively engage in career coaching and senior data scientists act as mentors within the team and throughout the organization.

 

New York Life has an active data science community with the opportunity to share one’s expertise and to learn from other groups. The Data Science Academy and Executive Education Program aim to educate employees and executive officers in the field of data science. The Women in Data Science group provides support to the current crop of women data scientists and encourages women not currently in the field of data science to explore professional and educational opportunities in data science. CDSAi also hosts numerous talks such as their lunch-and-learn series, as well as twice-yearly half-day data science expos and forums, to communicate the wide range of interesting and challenging data science projects that are conducted throughout the company.

 

 

Responsibilities

  • 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

  •      Master’s degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics, quantitative psychology, or operations research and 3 years of relevant industry experience
  • OR Ph.D. with concentration in similar fields, OR Associateship/Fellowship in one of the Actuarial Societies and 5 years of relevant industry 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 (data, IT, actuarial, medical, underwriting, Legal, Agency, government relations, etc.) as well as third-party data partners.
  •     Substantial programming experience with almost all of the following: R, Python, SPARK, SQL, other Hadoop. Exposure to GitHub.
  •     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, bootstrap).
  •      Experience with data visualization (e.g. R Shiny, Spotfire, Tableau)
  •     Proficiency in creating effective and visually appealing PowerPoint presentations.

 

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 our Foundation. 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: 84044

 

 

 


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