AVP – Advanced Analytics & AI Strategy Insurance

Vela Insurance Services provides specialized Excess and Surplus Lines Casualty and Professional Liability insurance solutions in the following market segments: Construction Specialty Casualty & Professional Liability. We offer national service and local knowledge to our exclusive wholesale broker network and the businesses they serve.

Based in either our Scottsdale AZ or Chicago IL offices the AVP Advanced Analytics & AI Strategy is the strategic and technical leader responsible for advancing AIdriven intelligence across underwriting claims and operations to transform portfolio decisionmaking into a datadriven cointelligence platform that delivers optimal riskadjusted returns.

Reporting to the Chief Actuary this role partners closely with the Senior Leadership Team including the President CUO Underwriting Segment Leaders CAO and CCO to cocreate analyticsenabled portfolio strategies that balance growth and profitability and support shared accountability for portfoliolevel P&L outcomes.

The AVP leads a team responsible for the development and deployment of advanced analytics machine learning and intelligence solutions that inform portfolio segmentation pricing adequacy claim severity management and operational efficiency.

This role ensures insights are operationalized into underwriting claims and portfolio levers that strengthen discipline improve outcomes and enable deliberate portfolio optimization across market cycles.

This position requires a handson data science leader and change agent who drives adoption of intelligent tools shapes enterprise AI strategy and fosters a culture of disciplined datadriven decisionmaking.

The AVP Advanced Analytics & AI Strategy plays a critical role in defining and scaling the future of analytics across Vela.

• Lead the team in the design deployment and continuous improvement of intelligence solutions that deliver measurable outcomes across underwriting claims and operations.
• Develop and execute the analytics roadmap including structured and unstructured data integration variable selection and alignment with Velas strategic priorities.
• Partner with the Senior Leadership Team to support portfolio oversight and optimize riskadjusted returns through analyticsdriven insights.
• Oversee the integration of intelligence into core underwriting and claims workflows ensuring full leverage of Kalepa Helix and enterprise data assets.
• Champion adoption of datadriven decisionmaking through effective change management and stakeholder engagement.

• Partner with Underwriting to design validate and refine risk factors embedded within underwriting intelligence platforms to improve portfolio performance.
• Enhance risk scoring pricing precision portfolio targeting and underwriting dashboards to support disciplined and profitable risk selection at both the risk and portfolio level.
• Partner with the CCO to advance claim analytics focused on handling efficiency reserving accuracy and claim settlement outcomes.
• Deliver insights on claim trends early warning indicators fraud detection and leakage to inform underwriting claims and portfolio strategy.

• Advance portfolio management capabilities to support capital objectives including the refinement of AIenabled rulesbased engines.
• Enable dynamic portfolio management through continuous forward-looking adjustment of risk selection pricing appetite and capacity based on risk insights and market conditions.
• Establish dynamic underwriting audits at the individual risk and portfolio level.
• Provide senior leadership with clear timely insights to support portfolio optimization and strategic decisionmaking.

• Lead advanced analytics and machine learning initiatives including model development monitoring recalibration and continuous improvement.
• Build scalable intelligence capabilities that embed feedback loops into execution in partnership with EsTech BTS and DNA teams at Berkley.
• Drive operational efficiency by identifying process gaps optimizing workflows and implementing automation and intelligence solutions.
• Identify prioritize and develop AI use cases including actionable prompts and intelligence tools that improve speed quality and consistency of execution.
• Partner with enterprise technology and data teams to ensure data quality accessibility architectural alignment and adherence to enterprise standards.

• Bachelors or Masters degree in Data Science Statistics Actuarial Science Computer Science Engineering or related quantitative field
• 710 years of experience applying data science advanced analytics or AI/ML in an insurance environment with demonstrated impact on underwriting claims pricing adequacy and portfolio performance
• Proven leadership experience building or managing analytics data science or operationalefficiency teams.
• Expertise in SQL Python machine learning frameworks and modern data platforms (e.g. Databricks cloudbased analytics environments).
• Strong understanding of underwriting claims risk modeling or actuarial concepts preferred.
• Experience with dashboarding and reporting tools such as Power BI.
• Demonstrated ability to translate business needs into analytical solutions and communicate complex concepts to nontechnical stakeholders.
• Track record of driving change management influencing crossfunctional teams and implementing new technologies or processes.
• Strong problemsolving criticalthinking and strategicplanning skills with the ability to operate both handson and at an enterprisestrategy level.

The Company is an equal employment opportunity employer.