Senior Data Scientist, Insurance & Advanced Analytics

Mapfre; Webster (MA); On-site; USD 130,000 - 160,000; Full time

Benefits offered by this job

Paid Time Off (PTO)

401(k) & Profit Sharing

Medical, Dental and Vision Coverage

Wellness programs

Job summary

Mapfre is seeking an analytics leader to design, build, and scale ML-focused solutions for complex insurance problems. The role requires deep ML, Python, and SQL expertise, plus strong business acumen and domain knowledge.

The candidate will own problems end-to-end, dive into data systems, remove blockers, and communicate clearly with stakeholders. Familiarity with GenAI concepts and agentic AI is a plus.

Qualifications

• Bachelor's degree in statistics, mathematics, data science, economics, finance, engineering, or related field.
• 8+ years of relevant experience, or a Master's degree with 2+ years.
• Property & Casualty Insurance experience.
• Strong predictive modeling, machine learning, and statistical analysis.
• Experience owning models in production and MLOps.
• Excellent communication to senior stakeholders.

Responsibilities

• Lead development and deployment of predictive models and ML solutions.
• Identify data misalignments, root causes, and improve model performance.
• Apply Python and SQL to explore data, engineer features, build models, and automate workflows.
• Monitor model performance, reliability, and production stability.
• Present model results and business impact to leadership.
• Develop prompts and GenAI workflows; explore new AGI techniques.
• Mentor junior team members and promote best practices.

Skills

Predictive modeling

Machine learning

Python

SQL

Data structures

MLOps

Communication

Leadership

Education

Bachelor's degree in statistics/math/data science/engineering

Master's degree in related field

Job description

Mapfre is seeking an analytics leader to design, build, and scale ML-focused solutions for complex insurance problems. The role requires deep ML, Python, and SQL expertise, plus strong business acumen and domain knowledge.

The candidate will own problems end-to-end, dive into data systems, remove blockers, and communicate clearly with stakeholders. Familiarity with GenAI concepts and agentic AI is a plus.