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VP, Model Monitoring & Performance

Chubb

VP, Model Monitoring & Performance

full-timePosted: Jul 17, 2026Updated: Aug 29, 2026Philadelphia, PA, United States

Job Description

*The ideal candidate will sit in one of the listed locations. However, remote arrangements will be considered. *The title and career band/level for this position are flexible based on the candidate’s experience.About the RoleAs our rating capabilities continue to expand across lines, we are investing in enhancing the next layer: a production-grade capability to measure model performance and feed those insights back into how we build, refine, and deploy them.The VP, Model Monitoring & Performance will lead this function. This leader will monitor model performance monitoring across all commercial lines, direct the building of the commercial data foundation that enables it, and translate performance insights into action.This is a builder role spanning BOP, Commercial Property, General Liability, Workers Compensation, and Commercial Auto, with goals to expand more broadly in the future. The opportunity is to establish best-in-class monitoring capabilities and single source of truth that supports the next phase of our rating strategy. What You Will OwnModel Performance MonitoringDesign and stand up a production-grade monitoring framework across all deployed commercial rating modelsDefine the metrics that matter: charge-to-model, actuarial adequacy by segment, loss ratio performance, model drift, lift validation, and segmentation effectivenessTranslate monitoring outputs into actionable recommendations for model refinement, filing strategy, and underwriting guidanceEstablish cadences, thresholds, and escalation paths that drive decisions, not just reportsCommercial Data Strategy & EnablementSet direction for the commercial data foundation: policy attributes, charged premium, rerate tables, loss experience, and exposure dataDirect multiple in-flight workstreams; align them around a coherent architecture and roadmapPartner with Actuarial data transformation initiatives. Drive toward a single source of truth for commercial rating data, unlocking access for the broader rating sophistication team and downstream enterprise dashboardingActionable Insight & InfluenceConvert performance data into clear, executive-ready narratives that inform decisions on rate, segmentation, and model investmentServe as the trusted voice on model performance for the Chief Actuary and the broader business leadership teamBuild feedback loops so that monitoring insights systematically improve future model development and filingsOperating Model & Cross-Functional PartnershipPartner closely with Data & Analytics teams to establish a clear operating model, proactively collaborating with the business while complementing, enterprise data capabilitiesLead a squad of data analysts, actuaries, and data engineers, directly and via dotted-line relationships, growing the team as the function matures 10+ years of progressive experience in insurance analytics, actuarial, data science, or model performance functions, with meaningful leadership experienceHands-on mastery of SQL and Python, and fluency operating in AI-native workflows (Claude Code, Cursor, or equivalent). This leader must be able to navigate complex data environments from day one, not just direct others to do soProficiency with at least one major data visualization platform (Tableau, Power BI, Qlik, or equivalent)Strong data architecture instincts; knowing what to curate, what to leave alone, and how to design for both monitoring and downstream useDemonstrated experience navigating highly fragmented data environments, including stitching together exposure, premium, and loss data across many legacy policy administration systemsTrack record of directing multiple concurrent workstreams and setting architectural and analytical direction across themStrong executive communication skills and the ability to translate technical performance data into clear business narrativesExperience operating in a regulated, multi-stakeholder environment where speed, rigor, and compliance must coexist Preferred:P&C insurance background with exposure to commercial linesFamiliarity with filed rating plans and rating bureau frameworksExperience with Databricks, Snowflake, or comparable cloud data platformsExperience building a function from a low baselineBackground in financial services analytics with clear aptitude and willingness to learn the commercial insurance domainWhat Success Looks LikeYear 1: Production monitoring capability stood up across highest-priority lines; charge-to-model and loss ratio performance reporting in place; commercial data foundation roadmap aligned and progressing; operating model with Data & Analytics establishedYear 2+: Monitoring insights routinely drive model refinement, filing decisions, and underwriting guidance; single source of truth for commercial rating data is established and adopted; measurable improvement in rate adequacy and segmentation effectiveness attributable to this function The pay range for the role is $170,000 to $250,000. The specific offer will depend on an applicant’s skills and other factors. This role may also be eligible to participate in a discretionary annual incentive program. Chubb offers a comprehensive benefits package, more details on which can be found on our careers website. The disclosed pay range estimate may be adjusted for the applicable geographic differential for the location in which the position is filled.

Locations

  • Philadelphia, PA, United States
  • Jersey City, NJ, United States
  • Whitehouse Station, NJ, United States
  • Philadelphia - 2000 Arch St

Salary

170,000 - 250,000 USD / yearly

Skills Required

  • insurance analyticsintermediate
  • at least one major data visualization platformintermediate
  • filed rating plansintermediate
  • Databricksintermediate
  • function from a low baselineintermediate
  • financial services analytics with clear aptitudeintermediate

Required Qualifications

  • 10+ years of progressive experience in insurance analytics, actuarial, data science, or model performance functions, with meaningful leadership experience (experience, 10 years)
  • Hands-on mastery of SQL and Python, and fluency operating in AI-native workflows (Claude Code, Cursor, or equivalent). This leader must be able to navigate complex data environments from day one, not just direct others to do so (degree in ai)
  • Proficiency with at least one major data visualization platform (Tableau, Power BI, Qlik, or equivalent) (experience)
  • Strong data architecture instincts; knowing what to curate, what to leave alone, and how to design for both monitoring and downstream use (experience)
  • Demonstrated experience navigating highly fragmented data environments, including stitching together exposure, premium, and loss data across many legacy policy administration systems (experience)
  • Track record of directing multiple concurrent workstreams and setting architectural and analytical direction across them (experience)
  • Strong executive communication skills and the ability to translate technical performance data into clear business narratives (experience)
  • Experience operating in a regulated, multi-stakeholder environment where speed, rigor, and compliance must coexist (experience)
  • P&C insurance background with exposure to commercial lines (experience)
  • Familiarity with filed rating plans and rating bureau frameworks (experience)
  • Experience with Databricks, Snowflake, or comparable cloud data platforms (experience)
  • Experience building a function from a low baseline (experience)
  • Background in financial services analytics with clear aptitude and willingness to learn the commercial insurance domain (experience)
  • Year 1: Production monitoring capability stood up across highest-priority lines; charge-to-model and loss ratio performance reporting in place; commercial data foundation roadmap aligned and progressing; operating model with Data & Analytics established (experience)
  • Year 2+: Monitoring insights routinely drive model refinement, filing decisions, and underwriting guidance; single source of truth for commercial rating data is established and adopted; measurable improvement in rate adequacy and segmentation effectiveness attributable to this function (experience)

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