Data Scientist III- Insurance & Advanced Analytics (Hybrid- Webster or Boston)

MAPFRE•Webster, MA

1d•$130,000 - $160,000•Hybrid

About The Position

We are looking for a forward-thinking analytics leader to design, build, and scale analytical solutions that solve complex, high-impact business problems. This role requires strong technical depth in machine learning, Python, and SQL, along with business acumen and insurance domain knowledge. The successful candidate will take ownership of problems from discovery through implementation, develop a deep understanding of complex data systems, look beyond surface-level results, proactively identify and work through blockers, and communicate clearly with team members and stakeholders. Familiarity with Generative AI concepts, prompt engineering practices, and emerging agentic AI approaches is a big plus.

Requirements

Bachelor’s degree in Statistics, Mathematics, Data Science, Economics, Finance, Engineering, or a related quantitative field (required), with either 8+ years of relevant experience, or a Master’s degree with 2+ years of relevant experience
Must have Property & Casualty Insurance experience
A results-driven mindset with the persistence to dig deeply into problems, identify root causes, and work proactively toward solutions
Deep expertise in predictive modeling, machine learning, and statistical analysis and technical details required to build reliable solutions
Strong experience working with complex data structures (sparse, high-dimensional, and time-series data)
Solid insurance domain knowledge is required, with claims experience highly preferred
Experience with prompt optimization, evaluation and refinement
Proven ability to solve ambiguous, complex problems with minimal direction and high autonomy
Strong communication skills, with the ability to translate complex analytics into clear business insights for senior stakeholders
Experience owning and managing models in production environments, including monitoring and MLOps practices
Demonstrated ability to innovate, research new techniques, and apply them to real-world business problems
Experience mentoring team members and influencing best practices across teams
Strong organizational and project management skills, with the ability to prioritize high-value work

Nice To Haves

Familiarity with Generative AI concepts, prompt engineering practices, and emerging agentic AI approaches is a big plus.
Claims experience highly preferred

Responsibilities

Lead the development and deployment of advanced predictive models and machine learning solutions for complex business challenges
Identify data misalignments, investigate root causes and develop targeted solutions to improve model performance. Proactively address blockers, evaluate alternatives, and work with the appropriate partners to move solutions forward
Apply strong Python and SQL skills to explore data, engineer features, build models, automate workflows, and validate results
Measure economic impact and partner with business teams to define KPIs and ensure value realization
Design processes and tools to monitor model performance, reliability, and stability in production
Present model performance, business impact, and analytical solutions to senior leadership
Develop, test, and refine prompts, and support the design of agent-based GenAI workflows
Conduct research into innovative algorithms and GenAI approaches to unlock new opportunities and use cases
Develop internal tools and programs to accelerate deployment, retraining, and scaling of models (MLOps), supporting both batch and real-time environments
Collaborate cross-functionally and serve as the key liaison with IT to implement and scale solutions
Create executive-ready presentations and detailed technical documentation to communicate results and best practices
Mentor and guide junior team members while promoting best-in-class modeling and statistical techniques
Partner with data governance and business teams to improve data quality, feature engineering, and overall data strategy
Identify and evaluate new data sources and emerging analytical techniques to maintain competitive advantage
Advocate for a data-driven culture and continuous innovation across the organization