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Plymouth Rock Assurance · 1 week ago

Lead Data Scientist

Boston, MA

Full-time

Onsite

Senior Level, Lead/Staff

$154K/yr - $204K/yr

Plymouth Rock Assurance is an Insurtech start-up within a well-established insurance company, focused on revolutionizing homeowners insurance. The Lead Data Scientist will own the predictive modeling process, collaborate with business leaders, and drive pricing and underwriting strategies using data-driven insights.

Auto InsuranceFinancial ServicesInsurance

H1B Sponsor Likely

Responsibilities

Own the end-to-end predictive modeling process, from business problem definition and data acquisition to deployment and performance monitoring

Collaborate directly with business leaders, product owners, and cross-functional stakeholders to align modeling strategies with business goals

Translate complex modeling results into actionable insights for technical and non-technical audiences alike

Work hands-on with large insurance datasets to uncover pricing and segmentation opportunities

Lead the discovery, evaluation, and incorporation of new data sources and methods, including third-party vendor collaborations

Monitor model performance, perform root-cause analysis, and iterate on solutions to enhance business outcomes

Champion best practices in coding, reproducibility, and documentation using modern analytics infrastructure

Incorporate Artificial Intelligence into your daily work to drive innovation, insights, and speed-to-market

Qualification

Predictive modelingPythonSQLCloud computing (AWS)Data visualizationStatistical modelingData wranglingCollaboration with stakeholdersRoot-cause analysisCommunication

Required

Proven ability to work independently, owning the entire modeling lifecycle

Fluency in Python (preferred) and R, including experience with production-ready modeling code and analytical pipelines

Expert-level SQL skills for large-scale data transformation and aggregation

Solid experience with cloud computing tools (especially AWS: S3, EC2, SageMaker) and Snowflake

Mastery of GLMs and GBMs (e.g., H2O, XGBoost, LightGBM); familiarity with clustering, Bayesian inference, regularization, and optimization a plus

Comfort working within Git-based, version-controlled environments

Strong grasp of relational databases and experience working with large, multi-source insurance datasets

Excellent communication skills, with experience presenting complex findings to senior executives

Master's or PhD in a quantitative field (e.g., STEM, Economics) strongly preferred

Prior knowledge of homeowners insurance and/or pricing frameworks is a plus

Preferred

Experience with tiering logic and segmentation beyond core risk pricing

Exposure to regulatory concerns regarding insurance pricing models and variable selection

Expertise in data visualization using tools like Plotly and Seaborn

Experience collaborating with non-technical stakeholders to drive decision-making

Experience using Artificial Intelligence tools both in super-charging your work and delivering results for the business

Benefits

Paid time off

Free onsite gym at our Boston location

Tuition reimbursement

Low cost and excellent health insurance coverage options that start on Day 1 (medical, dental, vision)

Robust health and wellness programs

Auto and home insurance discounts

Matching donation opportunities

Annual 401(k) employer contribution

Various Paid Family leave options including Paid Parental Leave

Resources to promote professional development

Convenient locations and pre-tax commuter benefits

Company

Plymouth Rock Assurance

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Founded in 2001

Boston, Massachusetts, USA

1001-5000 employees

https://www.plymouthrock.com

H1B Sponsorship

Plymouth Rock Assurance has a track record of offering H1B sponsorships. Please note that this does not guarantee sponsorship for this specific role. Below presents additional info for your reference. (Data Powered by US Department of Labor)

Distribution of Different Job Fields Receiving Sponsorship

Represents job field similar to this job

Trends of Total Sponsorships

2025 (11)

2024 (12)

2023 (6)

2022 (7)

2021 (5)

2020 (12)