Director of Data Science and Analytics
Location: New York
When you join our fantastic client, you’re joining a company that values development, career growth, collaboration, innovation, and diversity & inclusion. They are a growing entrepreneurial department which aims to design, create and offer innovative data-driven solutions for many parts of the enterprise. They’re are aided by their existing business with a large market share in individual life insurance. They have the freedom to explore external data sources and new statistical techniques, and are excited about delivering a whole new generation of Analytical solutions.
In fact, they’re designing and will build one of the first multivariate model-based continuous risk differentiations in the industry. This model will incorporate current underwriting best practices (including medical rules) as features and add other data sources, patterns/ideas and variables to essentially create a rating plan to support the next generation underwriting process. This is just one of several projects with large business value. 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. Their products will be implemented into real-time core business processes and decisions that drive the company (e.g. underwriting, pricing, agent recruiting, prospecting, new product development). They work with data ranging from demographics, credit and geo data to detailed medical data (medical test results, diagnosis, prescriptions) and social media information. They 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 be part of the transformation of an industry.
You will apply your highly developed analytical skills to work on all aspects of Agency analytics, ranging from agent recruitment and retention AI models, 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 Agency organization. You will apply your leadership experience, high energy level and business sense to supervise staff, 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.
- 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.
- 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 AI/statistical techniques to create high-performing predictive models and creative analyses to address business objectives and client needs.
- Works closely with Agency, Digital, IT and other groups 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: may manage 1-3 direct reports responsible for Agency data science. Manages staff including goal setting, performance evaluation, effective resource allocation and career/skill development, hiring and training.
- 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%).
- Graduate-level degree with concentration in a quantitative discipline such as statistics, computer science, mathematics, economics, physics, or operations research
- 10 + years of experience with predictive analytics in financial services or insurance (preferred but not mandatory) using large and complex datasets.
- 2+ years of management experience. 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.
- Demonstrated success in creating measurable business benefit for analytics while interacting with many stakeholders in a complex organization.
- 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, Agency, Legal, government relations, etc.) as well as third-party data partners.
- Demonstrated experience in strategic and analytical leadership. Executive presence on high-level meetings. Credible functional expertise in predictive analytics.
- Strong expertise in statistical modeling techniques such as linear/logistic regression, GLM, Deep Learning, 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, CV, bootstrap).
- Substantial programming experience with several of the following: Python, R, PySpark, TensorFlow and/or PyTorch, SQL, other Hadoop. Exposure to GitHub, Domino Data Labs.
- Experience with data visualization (e.g. R Shiny, Spotfire, Tableau)
- Proficiency in creating effective and visually appealing PowerPoint presentations.