Enterprise Data Science Lead: High-Impact ML

plymouthrock; Boston (MA); On-site; USD 152,000 - 217,000; Full time

Benefits offered by this job

4 weeks PTO + 9 holidays

Onsite gym

Tuition Reimbursement

Health insurance Day 1 coverage

401(k) contributions

Parental leave

Professional development

Job summary

Plymouth Rock Assurance seeks a Lead Data Scientist to own end-to-end data projects, from framing to deployment, in a fast-paced, entrepreneurial team. You will work on high-impact analytics across Product, Pricing, Underwriting, Claims, and Marketing, delivering production-grade solutions using modern ML/AI methods.

Senior leaders will expect you to mentor others, elevate engineering standards, and translate complex data into actionable business decisions.

Qualifications

• PhD in a quantitative field.
• Strong foundation in statistics and applied modeling.
• Hands-on experience with Python or R for statistical modeling and SQL for data analysis.
• Experience with ML/AI (NLP/LLMs, deep learning) is helpful but not required.
• Proven ability to deliver end-to-end models into production and monitor them.

Responsibilities

• Identify and frame high-value problems across functional areas.
• Develop, test, and deploy predictive models for growth and performance.
• Apply modern ML/AI techniques to accelerate development and capabilities.
• Build production-ready data pipelines, features, and monitoring.
• Communicate results clearly to technical and non-technical stakeholders.
• Mentor teammates and shape technical direction where applicable.

Skills

PhD preferred

Statistics

ML modeling

Python

SQL

Cloud AWS

Data storytelling

Education

PhD in quantitative field

Tools

H2O

XGBoost

LightGBM

SageMaker

Snowflake

Job description

Plymouth Rock Assurance seeks a Lead Data Scientist to own end-to-end data projects, from framing to deployment, in a fast-paced, entrepreneurial team. You will work on high-impact analytics across Product, Pricing, Underwriting, Claims, and Marketing, delivering production-grade solutions using modern ML/AI methods.

Senior leaders will expect you to mentor others, elevate engineering standards, and translate complex data into actionable business decisions.