Data Scientist (Hybrid Worcester, MA or Remote

Data Scientist (Hybrid Worcester, MA or Remote)

Worcester, MA, USA

Posted Tuesday, August 11, 2026 at 4:00 AM

For more than 170 years, The Hanover has been committed to delivering on our promises and being there when it matters the most. We live our values every day, demonstrating we CARE through our values, Sustainability initiatives and inclusive corporate culture .

Our Personal Lines team is currently seeking a Data Scientist in our Worcester, MA office on a hybrid arrangement or fully remote work location. This is a full-time, exempt role.

Join a Team Where Data Drives Strategy:

At The Hanover, data science is a key driver of how we understand risk, improve customer experiences, and make smarter business decisions. We're looking for a curious, analytical, and collaborative Data Scientist to join our Personal Lines Analytics team.

In this role, you'll apply advanced analytics, machine learning, and statistical modeling techniques to solve meaningful business challenges across our Personal Lines organization. You'll work alongside business leaders, product managers, actuaries, and data scientists to transform complex data into actionable insights that influence underwriting, pricing, customer experience, and growth strategies.

This is an opportunity to work with large and complex datasets, develop production-ready analytical solutions, and help shape the future of a data-driven insurance organization.

Why Join The Hanover?

• Work on high-impact analytics projects that directly influence business strategy and outcomes.
• Partner with experienced data scientists, actuaries, and business leaders across the organization.
• Access large-scale datasets and real-world business challenges that offer meaningful analytical opportunities.
• Grow your technical and business skills while developing expertise in predictive analytics and machine learning.
• Be part of a collaborative team that values innovation, continuous learning, and knowledge sharing.
• Help modernize how a leading insurance organization uses data to serve customers and manage risk.

IN THIS ROLE, YOU WILL:

• Develop and deploy predictive models, machine learning solutions, and statistical analyses to solve business problems.
• Explore large datasets to identify patterns, trends, opportunities, and risks that drive business performance.
• Partner with Personal Lines leaders and cross-functional stakeholders to understand business objectives and translate them into analytic solutions.
• Design experiments, conduct exploratory analyses, and evaluate model performance to generate actionable insights.
• Research and apply emerging data science methods, tools, and technologies to enhance business outcomes.
• Communicate findings and recommendations through compelling visualizations, presentations, and storytelling tailored to technical and non-technical audiences.
• Collaborate with data engineers and analytics partners to develop scalable, efficient, and sustainable analytical solutions.
• Contribute to a culture of continuous learning, innovation, and analytical excellence.

WHAT YOU NEED

TO APPLY:

Required Qualifications

• Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science, Analytics, Economics, or a related quantitative field.
• 2-6 years of experience applying data science, machine learning, advanced analytics, or statistical modeling in a business environment.
• Experience using Python and/or R for data analysis and model development.
• Strong foundation in statistical analysis, predictive modeling, machine learning, and data mining techniques.
• Experience working with large datasets and relational databases.
• Ability to translate business questions into analytical approaches and communicate results effectively.
• Strong problem-solving skills and intellectual curiosity.

Preferred Qualifications

• Master's degree in Data Science, Statistics, Applied Mathematics, Computer Science, or a related field.
• Experience building and deploying machine learning models in production environments.
• Familiarity with cloud-based analytics platforms and modern data science workflows.
• Insurance, financial services, or other risk-based industry experience.
• Experience with data visualization…