Job Description:
Providing for loved ones, planning rewarding retirements, saving enough for whatever lies ahead – our policyholders count on us to be there when it matters most. It’s a big ask, but it’s one that we have the power to deliver when we work together. We collaborate and innovate – pushing one another to transform not just Pacific Life, but the entire industry for the better. Why? Because it’s the right thing to do. Pacific Life is more than a job; it’s a career with purpose. It’s a career where you have the support, balance, and resources to make a positive impact on the future – including your own.
We're actively seeking a talented Sr. Business Analyst to join our Advanced Analytics team. This role is on-site 4 days per week and work from home 1 day per week in Newport Beach, CA. If you are not currently located near one of our offices, we offer comprehensive relocation assistance.
As a Sr. Business Analyst, you'll serve as the business-facing partner for Advanced Analytics across our Consumer Markets Division. Sitting at the front of the house, you'll uncover business initiatives, pain points, and value drivers across Finance, Underwriting, Sales, Product, and Fraud — then orchestrate the right analytics solutions by engaging our Analytics Engineering, Data Visualization, and Data Science teams. You'll own each initiative end-to-end against a delivery timeline and continue evolving solutions long after launch. Success in this role depends on close collaboration — uniting business stakeholders, Analytics Engineering, Data Visualization, and Data Science teams around a shared goal and ensuring every team is aligned on priorities, scope, and outcomes.
How you’ll help us move forward:
Build trusted relationships with stakeholders across Finance, Underwriting, Sales, Product, and Fraud — becoming the go-to analytics partner for each vertical.
Uncover business initiatives, pain points, and value measurements through active discovery — diagnosing the real problem before any solution is scoped.
Translate business needs into clear analytics requirements, success criteria, and prioritized delivery roadmaps that align to enterprise goals.
Orchestrate delivery by engaging Analytics Engineering, Data Visualization, and Data Science teams — defining scope, sequencing work, and removing blockers without taking on hands-on build responsibilities.
Own each initiative end-to-end against a defined delivery timeline — managing milestones, risks, and stakeholder communication from intake through adoption.
Drive continuous improvement post-launch by tracking adopt