Business Analyst Consultant - Advance Analytics

Pacific Life•Newport Beach, CA

1d•$152,010 - $185,790•Onsite

About The Position

As a Business Analyst Consultant - Advanced Analytics, 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.

Requirements

8+ years of experience as a Business Analyst, Analytics Manager, Solutions Owner, Analytics Delivery Manager, Product Owner, or similar business-facing analytics role.
4-year degree or equivalent experience.
Proven ability to engage business stakeholders, diagnose pain points, and translate needs into clear analytics requirements and delivery plans.
Demonstrated experience owning analytics initiatives end-to-end — managing scope, milestones, risks, and stakeholder communication across multiple teams.
Strong working understanding of Snowflake (or comparable cloud data warehouse) as a consumer — able to navigate data structures, validate outputs, and communicate fluently with engineering partners.
Strong working understanding of modern BI platforms (Tableau and Power BI) — able to interpret dashboards, validate visualizations, and partner effectively with visualization teams.
Experience partnering with Analytics Engineering, Data Engineering, or Data Visualization teams to deliver analytics products.
Track record of defining success metrics, tracking adoption, and reporting measurable business outcomes.
Excellent communication and storytelling skills across analysts, managers, and executive audiences.
Comfortable navigating ambiguity and balancing multiple initiatives simultaneously.

Nice To Haves

Hands-on fluency with Snowflake and modern BI platforms (Tableau, Power BI) — confident running queries, validating results, and partnering credibly with engineering teams.
Working knowledge of AI tools, LLMs, and AI agents — including the ability to identify practical use cases that improve analytics delivery or stakeholder self-service.
Cross-functional credibility — able to translate fluently between business stakeholders and analytics engineering and visualization teams.
Demonstrated initiative-level ROI ownership — proving and communicating measurable business value, not just delivering features.
Domain depth in Finance, Underwriting, Sales, Product, or Fraud within financial services, insurance, or a similarly regulated industry.

Responsibilities

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 adoption, capturing feedback, and partnering with delivery teams on enhancements that evolve solutions over time.
Measure and communicate ROI — defining benefit metrics up front and reporting realized business value back to stakeholders and leadership.
Build deep domain expertise within supported verticals to anticipate needs, challenge assumptions, and recommend higher-value analytics opportunities.
Stay current on AI agents, GenAI tooling, and modern analytics patterns — identifying practical use cases that solve business problems.