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