AVP, Data Science

Berkley•Glen Allen, VA

20h•$132,000 - $189,000•Onsite

About The Position

The AVP, Data Science is a senior leader responsible for advancing analytics, AI, and machine learning capabilities across the Regional Segment. This role drives data-driven decision making, delivers measurable business impact, and partners with business and technology leaders to develop scalable solutions that improve underwriting, claims, operational efficiency, profitability, and customer outcomes. Key Responsibilities Define and execute the Regional Segment's data science strategy and roadmap aligned to business objectives. Partner with Underwriting, Claims, Actuarial, Product, and Operations leaders to identify opportunities and deliver measurable ROI. Lead the development, deployment, and governance of predictive analytics, machine learning, and AI solutions. Oversee the full model lifecycle, including development, validation, monitoring, and continuous improvement. Champion responsible AI practices, model governance, regulatory compliance, and analytics best practices. Collaborate with data engineering, enterprise analytics, and technology teams to scale data products and AI capabilities. Promote cross-functional adoption of analytics and foster a culture of data-driven decision making. Represent the Regional Segment in enterprise analytics and AI initiatives. Leadership Responsibilities Lead, mentor, and develop a high-performing team of Data Scientists and Data Engineers. Drive talent acquisition, performance management, succession planning, and career development. Foster a culture of innovation, collaboration, technical excellence, and continuous learning.

Requirements

Advanced degree (Master's or PhD) in a quantitative discipline — Data Science, Statistics, Mathematics, Computer Science, Economics, Actuarial Science, Operations Research, or equivalent — OR 7–10 years of demonstrated experience developing and deploying predictive, prescriptive, and machine learning models in a production environment.
Proven leadership of data science teams delivering measurable business results.
Expertise in machine learning, AI/GenAI, predictive modeling, and model lifecycle management.
Strong understanding of P&C insurance operations, including underwriting, claims, pricing, and actuarial functions.
Experience with AI governance, regulatory compliance, and responsible AI practices.
Proficiency in Python, R, SQL, Spark, and cloud-based analytics platforms (e.g., Databricks).
Strong data visualization and business intelligence skills (Power BI preferred).
Ability to analyze complex data and communicate insights effectively to both technical and executive audiences.
Demonstrated success building, developing, and mentoring high-performing teams.
Excellent leadership, collaboration, communication, and problem-solving skills.
Proficiency in Microsoft Office Suite and willingness to travel occasionally.

Responsibilities

Define and execute the Regional Segment's data science strategy and roadmap aligned to business objectives.
Partner with Underwriting, Claims, Actuarial, Product, and Operations leaders to identify opportunities and deliver measurable ROI.
Lead the development, deployment, and governance of predictive analytics, machine learning, and AI solutions.
Oversee the full model lifecycle, including development, validation, monitoring, and continuous improvement.
Champion responsible AI practices, model governance, regulatory compliance, and analytics best practices.
Collaborate with data engineering, enterprise analytics, and technology teams to scale data products and AI capabilities.
Promote cross-functional adoption of analytics and foster a culture of data-driven decision making.
Represent the Regional Segment in enterprise analytics and AI initiatives.
Lead, mentor, and develop a high-performing team of Data Scientists and Data Engineers.
Drive talent acquisition, performance management, succession planning, and career development.
Foster a culture of innovation, collaboration, technical excellence, and continuous learning.