Director, Advanced Analytics (Hybrid - Webster or Boston)

 

 

Summary:

 

 

Mapfre is seeking a visionary Director of Advanced Analytics to lead and shape our enterprise-wide AI strategy and execution. This highly visible leadership role blends deep actuarial expertise, advanced analytics, business acumen, and leadership to deliver impactful, data-driven solutions across underwriting, product, pricing, and more.

 

You’ll oversee a high-performing team of data scientists while remaining personally hands-on in model design, analytical problem solving, and technical reviews, partner closely with Product, Underwriting, and Actuarial leadership, and champion a culture of innovation, responsible AI, and continuous learning. From shaping the AI roadmap to actively building and reviewing models and delivering measurable business value, you’ll be at the forefront of transforming how actuarial and technical decisions are made through data, advanced analytics and AI.

 

 

Responsibilities:

 

 

• Lead AI Strategy & Execution
  Align enterprise-wide advanced analytics initiatives with business priorities, with a strong emphasis on product strategy, pricing, underwriting, while actively contributing to the design and implementation of key models that drive measurable impact.

 

• Drive Cross-Functional Collaboration
  Build and manage a structured AI engagement framework that enables close partnership between Actuarial, Product, Underwriting, Data Engineering, and IT, ensuring  while serving as a hands-on technical partner in deep-dive working sessions and solution design.

 

• Champion AI Literacy & Innovation
  Promote data-driven and model-informed decision-making within technical areas by educating the Technical Area stakeholders, leading by example through hands-on analytical work,  and fostering experimentation beyond traditional actuarial approaches.

 

• Translate Business Needs into Scalable AI Solutions
  Lead and directly contribute to the development of advanced analytics and AI use cases, from problem framing to solution design and performance monitoring, ensuring solutions complement actuarial judgment while improving predictive power, efficiency, and speed to market.

 

• Oversee Full Analytics Project Lifecycle
  Manage planning, execution, validation, and maintenance of analytics projects while personally reviewing model assumptions, methodology, performance, and limitations, ensuring alignment with actuarial standards, model risk management, regulatory expectations, and responsible AI principles.

 

• Advance MLOps & Responsible AI Practices
  Implement best practices with direct hands-on involvement on model development, deployment, monitoring, and retraining with a focus on fairness, explainability, and regulatory compliance.

 

• Expand AI Capabilities Through Partnerships
  Collaborate with internal teams and external partners, while maintaining internal technical ownership and the ability to independently assess, stress-test, and challenge vendor models.

 

• Lead & Develop High-Performing Teams
  Provide strategic leadership and mentorship to analytics teams, fostering a culture where leaders remain technically credible, hands-on, and actively involved in problem solving.

 

 

Qualifications:

 

 

• Actuarial background required; credentialed actuary (ACAS/FCAS or equivalent) strongly preferred.

 

• PhD (preferred) or Master’s in a quantitative field such as Actuarial Science, Statistics, Mathematics, Engineering, Computer Science, or related quantitative field.

 

• Minimum of 8 years of experience across actuarial, advanced analytics, or data science roles, including significant hands-on model development experience.

 

• Hands-on experience in any of these items: pricing, rate indications, product optimization, actuarial forecasting, loss modeling, profitability analysis, underwriting, risk selection and portfolio management.

 

• 3+ years of leadership experience managing high-impact data science or cross-functional teams (preferred), with continued personal technical contribut