VP, Model Monitoring & Performance

Chubb•Philadelphia, PA

5d•Remote

About The Position

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. As 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.

Requirements

10+ years of progressive experience in insurance analytics, actuarial, data science, or model performance functions, with meaningful leadership experience
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
Proficiency 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 use
Demonstrated experience navigating highly fragmented data environments, including stitching together exposure, premium, and loss data across many legacy policy administration systems
Track record of directing multiple concurrent workstreams and setting architectural and analytical direction across them
Strong executive communication skills and the ability to translate technical performance data into clear business narratives
Experience operating in a regulated, multi-stakeholder environment where speed, rigor, and compliance must coexist

Nice To Haves

P&C insurance background with exposure to commercial lines
Familiarity with filed rating plans and rating bureau frameworks
Experience with Databricks, Snowflake, or comparable cloud data platforms
Experience building a function from a low baseline
Background in financial services analytics with clear aptitude and willingness to learn the commercial insurance domain

Responsibilities

Design and stand up a production-grade monitoring framework across all deployed commercial rating models
Define the metrics that matter: charge-to-model, actuarial adequacy by segment, loss ratio performance, model drift, lift validation, and segmentation effectiveness
Translate monitoring outputs into actionable recommendations for model refinement, filing strategy, and underwriting guidance
Establish cadences, thresholds, and escalation paths that drive decisions, not just reports
Set direction for the commercial data foundation: policy attributes, charged premium, rerate tables, loss experience, and exposure data
Direct multiple in-flight workstreams; align them around a coherent architecture and roadmap
Partner 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 dashboarding
Convert performance data into clear, executive-ready narratives that inform decisions on rate, segmentation, and model investment
Serve as the trusted voice on model performance for the Chief Actuary and the broader business leadership team
Build feedback loops so that monitoring insights systematically improve future model development and filings
Partner closely with Data & Analytics teams to establish a clear operating model, proactively collaborating with the business while complementing, enterprise data capabilities
Lead a squad of data analysts, actuaries, and data engineers, directly and via dotted-line relationships, growing the team as the function matures