The Data Scientist may be responsible for leading or participating in the cross departmental collaboration to define and develop predictive modeling initiatives and building, refining, and improving existing models as well as developing new techniques and applications to different areas of the company. This position leads or participates with cross-departmental collaboration and communication of complex technical models as well as leads or participates with the implementation of the models on behalf of Actuarial & Advanced Analytics including interfacing with Information Services, Underwriting, Claims, Finance, and Sales.
Essential Duties & Responsibilities
Adapts and develops rating methodologies for both existing and new company products using advanced techniques to incorporate new variables, etc., in pursuit of a competitive advantage and creation of economic profit opportunities. Helps shape the overall advanced analytics strategy for the organization.
Identifies, retrieves, and prepares data in support of actuarial analysis through R, SQL, Essbase, and other data sources. Includes internal data (exposure, premium, loss, claims, price, etc.) and various forms of external data (bureau loss costs, bureau trends, macroeconomic data, market share, market pricing, etc.)
Ensures the accuracy and suitability of data for the business need at hand. Manipulates data, performs preliminary analysis and interprets data through various analytics platforms. Summarizes and presents recommendations.
Supports the transformation of business intelligence tools from static reporting to dashboards, increasing data visualization and availability, supporting cross-division collaboration, and operationalizing advanced analytics.
Supports the actuarial function in identifying segments with profitable growth potential and underperforming segments. Assists in proposing corrective actions to improve profitability.
Performs advanced analytics and modeling techniques including but not limited to generalized linear modeling and other forms of multivariate analysis. This role is expected to build, refine, and improve existing models as well as develop new techniques and applications to different areas of the company.
In additional to regular modeling responsibilities, this person will use critical thinking skills and apply advanced modeling techniques, including but not limited to AI/Machine Learning, to provide insights and solve business problems including techniques such as classification and regression trees, random forests, neural networks, clustering, and other machine learning techniques.
May participate in other departmental deliverables and activities such as enterprise risk management (including support for catastrophe management), economic capital modeling, rate reviews, loss reserving, and planning. Provides innovation and leadership when applicable.
Leads the innovation and efficiency efforts related to tools and analysis in support of Underwriting’s pricing decisions with respect to large accounts as well as small commercial portfolio price adequacy analyses.
Performs other related duties as assigned by management.
Bachelor's or Master Degree and/or technical degree in areas such as Computer Science, Math, Statistics, Applied Mathematics, or similar studies from a university; 5 years related experience with large data bases, analytical problem solving in a business environment, and with programming models and queries; or equivalent combination of education and work experience is required. Experience with SAS, SQL and other statistical software building models and manipulation of data. Experience in conceptualizing and designing models to address business needs.