Job summary
Job post source
This job is directly from Plymouth Rock Assurance
Job overview
The Lead Data Scientist role at Plymouth Rock Assurance is a high-impact position responsible for driving predictive modeling and data science initiatives to influence pricing and underwriting strategies within the company.
Responsibilities and impact
The Lead Data Scientist will own the end-to-end predictive modeling process, collaborate with business leaders and stakeholders, translate complex data into actionable insights, work with large insurance datasets, incorporate new data sources, monitor model performance, and champion best practices in analytics and AI integration.
Experience and skills
Candidates must have proven independent modeling experience, fluency in Python and R, expert SQL skills, cloud computing experience (AWS, Snowflake), mastery of GLMs and GBMs, familiarity with version control, strong communication skills, and preferably a Master's or PhD in a quantitative field; insurance knowledge is a plus.
Career development
The role offers high visibility with direct presentations to the CEO and collaboration with senior leadership, providing opportunities for strategic impact and professional growth within an innovative and entrepreneurial environment.
Work environment and culture
The company fosters an empowering, innovative, and entrepreneurial culture with a focus on technology investment and collaborative, cross-functional teamwork embedded within the product team.
Company information
Plymouth Rock Assurance is a well-established insurance company with over $2.5 billion in personal and commercial insurance written, employing over 2,000 people, headquartered in Boston, and rated A-/Excellent by A.M. Best.
Team overview
The Lead Data Scientist will join the Plymouth Rock Home team, an Insurtech start-up within the company, working closely with the VP of Product and senior leadership in a fast-paced, entrepreneurial setting.
Job location and travel
The company is headquartered in Boston, Massachusetts; specific remote or travel details are not provided.
Unique job features
This role is unique due to its full-stack autonomy over modeling processes, high visibility with direct CEO presentations, strategic impact on business outcomes, and integration of AI tools in an innovative, agile environment.
Company overview
Plymouth Rock Assurance is a regional insurance provider offering auto, home, and umbrella insurance primarily in the Northeastern United States. Founded in 1982, the company differentiates itself through customer-centric services, including innovative technology solutions and personalized customer care. They generate revenue by underwriting insurance policies and earning premiums from policyholders. Key historical milestones include the introduction of the Crashbusters® mobile claims service and the Door to Door Valet Claim Service®, which have set industry standards for convenience and efficiency.
How to land this job
Position your resume to highlight your leadership in end-to-end predictive modeling, emphasizing your ability to independently manage the full lifecycle from data acquisition to deployment and monitoring, as this is central to the Lead Data Scientist role at Plymouth Rock Assurance.
Emphasize technical expertise in Python, R, SQL, and cloud platforms like AWS and Snowflake, along with mastery of GLMs, GBMs, and experience with version control (Git), reflecting the job’s demand for deep data science skills and production-ready code.
Apply through multiple platforms, including Plymouth Rock Assurance’s corporate career site and LinkedIn, to maximize your application visibility and increase your chances of landing an interview.
Connect with members of the Product and Data Science teams at Plymouth Rock Assurance on LinkedIn; initiate conversations by referencing the company’s innovative approach to homeowners insurance or asking about how data science drives product strategy, making your outreach relevant and engaging.
Optimize your resume for ATS by incorporating keywords from the job description such as 'predictive modeling,' 'pricing and underwriting,' 'Python,' 'AWS SageMaker,' 'GLMs,' and 'data visualization,' ensuring your resume passes automated screenings effectively.
Leverage Jennie Johnson's Power Apply feature to automate tailored applications, identify multiple application avenues, and discover LinkedIn contacts to network with, allowing you to focus your energy on preparing for interviews and refining your skills.
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