Hiring: Lead Data Scientist Company: Plymouth Rock Assurance Location: Greater Boston Job Posted Time: 2026-09-16 15:03:34 Employment Type: On-site Target Skills & Keywords : AWS, Agile, Computer Vision, Data Pipeline, Deep Learning, EC2, Git, LLM, LightGBM, Machine Learning, NLP, Python, S3, SQL, SageMaker, Snowflake, XGBoost About the job Required Skills: •Identify and frame high-value problems across functional areas; translate business questions into analytical strategies, experiments, and measurable outcomes. •Develop, test, and deploy predictive models that drive profitable growth and improve operational performance across the enterprise. •Build production-ready solutions: robust data pipelines, feature engineering, measurement discipline (KPIs, guardrails, and experiment design), model monitoring, and clear, reproducible documentation aligned to best practices. •Communicate with impact: tell the story with data, present recommendations to technical and non-technical stakeholders, and influence decisions at senior levels. •Advance team excellence: evaluate new methods and tools, share reusable components, elevate engineering standards, and (at Senior/Lead) mentor others and help shape technical direction. Qualifications: •PhD in a quantitative field (PhD strongly preferred). •Strong foundation in statistics and applied modeling—you can connect theory to practical, business-relevant solutions. •Python (strongly preferred) and/or R for statistical modeling •SQL for large-scale data transformation and analysis •GLMs and tree-based methods/GBMs (e.g., H2O, XGBoost, LightGBM); familiarity with clustering, Bayesian methods, regularization, and optimization is a plus •Demonstrated capacity to deliver results in real-world settings: structured problem-solving, experimental mindset, and pragmatic decision-making. •Senior candidates must have a proven track record of end-to-end model ownership including shipping models into production, and improving them through monitoring, measurement, and iteration. •Strong communication skills—able to present and explain methods, assumptions, tradeoffs, and results clearly. •Strong grasp of relational databases and experience working with large, multi-source datasets. •Comfort working in Git-based, version-controlled environments; strong documentation practices are required. Compensation: •$152,000 - $217,000 / year Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!