Data Scientist (Hybrid)

The Data Scientist independently applies advanced analytics and machine learning techniques to solve complex business problems and support organizational decision-making. This role is responsible for developing and maintaining predictive models, analyzing complex datasets, and delivering actionable insights aligned with business objectives. The Data Scientist collaborates with cross-functional stakeholders to support analytical initiatives and recommend data-driven approaches to business challenges. This position may provide technical guidance to Associate Data Scientists and supports analytical best practices within the department. Duties & Responsibilities: Design, develop, test, deploy, and maintain predictive and analytical models. Perform advanced exploratory analysis, feature engineering, model evaluation, and statistical analysis to support analytical initiatives. Manage model lifecycle activities including validation, monitoring, documentation, and periodic retraining to ensure model effectiveness and reliability. Collaborate with data engineers and business partners to support scalable analytical workflows and processes. Design and evaluate experiments (e.g., A/B tests) to measure model and business performance. Analyze complex datasets to develop actionable insights and recommendations that support operational and business decisions. Support the identification of analytical opportunities and contribute to data-driven solutions for business challenges. Document analytical processes, model assumptions, and results to support reproducibility and governance standards. Contribute to knowledge sharing and provide guidance to Associate Data Scientists as appropriate. Stay informed on emerging data science tools, techniques, and industry best practices. Requirements: Bachelor’s degree in applied mathematics, data science/analytics, computer science, statistics, or related field, and 4 years of experience in insurance, analytics or data science. Qualifications/Skills: Proficiency in SQL, Python or R (Python preferred), and machine learning techniques. Strong analytical, problem-solving, and organizational skills. Ability to work independently and collaboratively within cross-functional teams. Ability to explain technical concepts and analytical findings to non-technical audiences. Understanding of statistical analysis, model evaluation, and responsible modeling practices. Experience with data visualization tools such as Tableau preferred. Familiarity with software engineering, cloud platforms, or database systems is a plus. Market Range: 14 / Exempt / 40 hours per week / Hybrid - 2 days in office Salary: $86,136 - $143,560 Accepting applications through: 9/3/26