Lead Data Scientist, Strategic Insurance Businesses

Key Skills

Java Programming, Python Programming, SQL, Apache Hadoop, Tableau, PySpark, R-Shiny, Github, Domino, Spotfire

Job Description

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.

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 insurance businesses (SIBs) which could gain enormous incremental value from our expertise providing us with 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 apply your highly developed analytical skills to work on all aspects of analytics within the SIBs, ranging from long term disability insurance, life insurance, annuities and investment sales analytics and optimization models, fraud/non-compliant behavior detection with machine learning, experimental design and other exciting data science work around the Strategic Insurance Businesses.

You will apply your leadership experience, high energy level and business sense to communicate with internal stakeholders and external vendors while effectively leading complex analytics projects. You will also ingest and wrangle data, propose analytics strategy, create related business cases, drive several large initiatives, build and implement solutions at scale and give presentations as a subject matter expert.

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

• Independently leads 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 stakeholders how analytics can be implemented to maximize business benefits. Provides support, which includes strategic consulting, needs assessments, project scoping and the preparation/presentation of analytical proposals.
• Drives 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.
• Utilizes advanced statistical/AI techniques to create high-performing predictive models and creative analyses to address business objectives and client needs.
• Works closely with business and technology partners in designing, building and implementing AI/data science 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 internal clients and stakeholders on project/test results, opportunities, questions. Resolves problems and removes obstacles to timely and high-quality project completion.
• Management track: potential to manage direct reports.
• Actively contributes to analytics strategy by contributing ideas, preparing presentation material for internal stakeholders, and product design/business case materials for NYL leadership.
• Follows industry trends in insurance and related data/AI 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.
• 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, operations, Legal, 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/logistic regression, GLM, survival analysis, tree-based 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, cross-validation, bootstrapping).
• 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, Spotfire) is a plus
• Proficiency in creating effective and visually appealing PowerPoint presentations.

Location

• Manhattan (NoMaD, walking distance from Penn Station and Grand Central Station). 
• Relocation is available.
• Two days per week remote-work starting in October.