Data Scientist - Predictive Modeling

March 5

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Kingstone Insurance Company

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Kingstone Insurance Company is a provider of specialized insurance products focused on protecting individual and business investments. With a commitment to customer service, they offer a variety of coverage options including homeowner policies, landlord policies, personal umbrella policies, and more. The company prioritizes policyholders' needs, ensuring access to a quick and efficient claims process and customizable insurance solutions.

Property and Casualty Insurance • Excellent personal service • Competitive rates and commission levels

51 - 200 employees

Founded 1886

💸 Finance

💳 Fintech

📋 Description

• Design, build, and deploy pricing, underwriting, and customer demand models to continuously improve Kingstone’s profitability and growth. • Oversee end-to-end model development and application. • Continuously refresh and enhance existing models. • Own data management for the modeling function, including data collection, integration, cleaning, processing and transformation. • Explore new data sources and analytical techniques to ensure competitive advantage. • Communicate analysis, insights, and results to team, business partners, and leaders. • Share expertise with the business and the actuarial community through discussions, presentations, or peer reviews to improve business outcomes.

🎯 Requirements

• An advanced degree in Statistics, Data Science, or a related field; or a bachelor’s degree with 4+ years of predictive modeling experience. • 2+ years of experience working in a data science modeling development position in the insurance field. • Experience working for a personal lines P&C insurance carrier, preferably with experience in the Homeowners business. • Expertise in Microsoft Office tools, SQL, and R or Python. • Hands-on modeling experience with large-scale datasets and a deep understanding of predictive modeling, data mining, and other quantitative and research analytics (Generalized Linear Models, Multivariate Analysis, Bayesian Methods, Non-Linear Models, Decision Trees, Parametric estimation, Machine learning techniques, etc.). • Intensive experience managing, processing and analyzing data for modeling purposes. • Industry expertise in predictive analytics tools, regression models, and software (preferably Earnix) is required. • Self-motivation and capability of independently and proactively advancing projects. • Strong willingness to learn and attention to detail. • Excellent communications skills including verbal, written, and presentation skills. • Collaborative strengths and ability to work as part of a team as well as cross-functionally. • Ability to develop and deliver communications for complex technical projects to non-technical audiences (appropriate audience, level of detail, urgency).

🏖️ Benefits

• Comprehensive health benefits • Life and disability insurance • 401(k) with company match • Paid parental leave • Paid vacation, paid holidays, and birthday off • Flexible work schedule • Peer recognition program