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Business Intelligence Analyst III, Marketing Analytics

Job in Livonia, Wayne County, Michigan, 48153, USA
Listing for: AAA Life Insurance Company
Full Time position
Listed on 2026-02-27
Job specializations:
  • IT/Tech
    Data Analyst, Data Science Manager
Salary/Wage Range or Industry Benchmark: 75000 - 95000 USD Yearly USD 75000.00 95000.00 YEAR
Job Description & How to Apply Below

Overview

Why AAA Life

AAA Life is a respected and trusted American brand that has been focusing on Life Insurance and Annuity Products since 1969. At AAA Life we have over 1.8 million policies where we take pride in earning the trust of our policyholders who understand our promise to be there for them – and their families – when we’re needed most. By joining the AAA Life team, you are joining a company that genuinely cares about helping each other, with a devotion to protect the lives of those around us.

We embrace a diverse, equitable, inclusive culture where all associates can feel a sense of belonging and use their unique talents and perspective to influence, innovate, motivate, and thrive.

How You’ll Work:
Hybrid

Relocation Eligibility:
Available

Responsibilities

What You'll Do:

As a Business Intelligence and Marketing Analyst, you will be responsible for delivering insights and recommendations related to the marketing of AAA Life’s various products. You will partner with marketing staff, marketing data managers, and other data analysts and data scientists to identify business questions, gather data, perform appropriate analyses, and deliver insights and recommendations. This role requires proficiency in SQL, R or Python, a visualization tool such as Power BI or Tableau, and a passion for delivering actionable insights and driving the growth of the organization.

  • Design, build, and automate user-friendly Power BI dashboards and management reports for stakeholders across all business functions, including Sales, Marketing, Product, Technology, and Operations. Ensure reporting enables data-driven decision-making at both tactical and strategic levels.
  • Deliver actionable insights that improve business performance at both the campaign and enterprise level. Translate complex analyses into clear strategic recommendations that drive measurable improvements in sales, profitability, operational efficiency, and competitive positioning.
  • Track marketing initiatives and produce comprehensive 360-degree campaign performance analyses. Validate results against forecasts and business plans, identify performance gaps and root causes, and recommend data-driven optimizations to improve outcomes.
  • Perform in-depth analyses to identify key business risks and opportunities. Provide clear recommendations to senior leadership to enhance overall profitability and strengthen operational effectiveness.
  • Distill complex data sets and relationships into clear, concise visualizations and executive-ready presentations that communicate insights effectively to both technical and non-technical audiences.
  • Implement key recommendations by:
    • Identifying and aligning cross-functional stakeholders
    • Translating business needs into technical and analytical requirements
    • Ensuring accurate implementation of solutions
    • Monitoring impact through performance measurement
    • Continuously optimizing results based on data
  • Gather, process, and analyze raw data at scale, including writing SQL queries, scripts, calling APIs, and performing web scraping where appropriate.
  • Transform structured and unstructured data into formats suitable for analysis, then conduct advanced statistical and performance analyses to extract meaningful insights.
  • Conduct advanced analytical techniques including customer segmentation, model and decile analysis, hypothesis testing (A/B and multivariate testing), and performance diagnostics to support strategic decision-making.
  • Support strategic planning through forward-looking analysis, scenario modeling, and performance forecasting to guide growth and investment strategy.
  • Partner with marketing, data, and technology teams to ensure data integrity, governance, and suitability for enterprise-level analytics.
  • Maintain clean and organized documentation of data, methodologies, and results in a central depository.
  • Identify and implement automation opportunities that improve efficiency, reduce manual effort, and accelerate time to actionable insight.
  • Provide backup support to data scientists and modelers as business needs require. Demonstrate comfort building statistical models and leveraging ML/AI platforms to enhance insight generation.
  • Actively seek…
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