You will apply your highly developed analytical skills to work on all aspects of the life insurance underwriting value chain, ranging from risk models, fraud detection, and process triaging to a variety of other analytics solutions.
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.
- Manages 1-3 direct reports responsible for insurance underwriting analytics, including exploration/consolidation of a variety of internal and external data (e.g. digital medical records, credit, social), triaging models and a variety of mortality models for automating most underwriting/risk classification decisions. Works closely with Underwriting, Actuarial, IT, Legal, Government relations and several other groups in designing, building and implementing these solutions.
- Drives the use of data-based decision making and Analytics within the clients by active internal partnership management, discovering business opportunity and creating business value by executing on high-priority projects.
- Utilizes advanced statistical techniques to create high-performing predictive models and creative analyses to address business objectives and client needs.
- 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.
- 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 the companies leadership.
- 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.
- 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, or operations research OR Fellowship in one of the Actuarial Societies (CAS or SOA).
- 7+ years of experience with predictive analytics in an insurance context using large and complex datasets. Experience with P&C personal lines rating plan modeling, health or life insurance is preferred.
- 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 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.
- 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 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).
- Substantial programming experience with several of the following: SAS (STAT, macros, EM), R, H2O, Python, SPARK, SQL, other Hadoop. Exposure to GitHub.
- Experience with data visualization (e.g. R Shiny, Spotfire, Tableau)
- Proficiency in creating effective and visually appealing PowerPoint presentations.