Director of Actuarial Data Scientist
We are looking to add a Life & Health Actuary with data science experience to our team. This role will be responsible for building actuarial and predictive analytics models from scoping initiatives to model deployment. He/She will work within the advanced analytics team and report to the Managing Director of Portfolio Analytics. The Predictive Analytics team is responsible for the development and implementation of predictive models to support pricing and underwriting. This position requires strong communication skills and applied pricing/modeling experience.
Utilizes actuarial models and advanced statistical techniques to create high-performing predictive models to address business objectives and automate processes. Tests new statistical analysis methods, software and data sources for continual improvement of quantitative solutions.
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. Assist in replacing and displacing spreadsheet-based approaches wherever feasible.
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.
Follows industry trends in insurance and related data/analytics processes and businesses. Functions as an analytics expert in meetings with other internal areas. Actively participates in proof of concept tests of new data, software and technologies. Shares knowledge within Portfolio Analytics group.
Improve reporting and visualization of analysis results for both internal and external audiences.
Education and Qualifications:
Masters /Bachelors degree in Actuarial Science and/or STEM field
Associateship/Fellowship in Society of Actuaries and 7+ years of relevant industry experience
Applied pricing, modeling and experience studies expertise
Strong business acumen and communication skills, as well as ability to effectively present technical concepts to non-technical individuals
Proven track record of developing complex actuarial models and predictive analytics models
Ability to connect deep data understanding with how to impact business decisions
Comfortable working in multidisciplinary teams. Ability to operate effectively through challenging or ambiguous situations.
Good organization and time management skills; ability to work independently.
Close attention to detail.
Strong commitment to teamwork, excellence, and personal/professional growth.
Advanced technical proficiency in Actuarial Science, Data Science, Programming, and Statistics
Substantial programming experience with most of the following: R, Python, SQL, Excel. Exposure to actuarial modeling software and 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. Familiarity with regularization techniques (Ridge, Lasso, elastic nets), variable selection techniques, feature creation (transformation, binning, high level categorical reduction, etc.) and validation (hold-outs, CV, bootstrap).
Ability to independently research relevant topics, enlighten the team based on findings, and convert findings to value-added deliverables
Ability to determine when to use a simple analytic solution and when to use advanced analytical solutions
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