Marketing Data Analytics Manager

UPS

2d•Onsite

About The Position

Lead enterprise Business Intelligence (BI) capabilities through the strategic use of AI, machine learning, and advanced analytics. This role manages BI, data engineering, and analytics to deliver scalable AI-enabled insights, decision intelligence platforms, and self-service analytics solutions that drive revenue growth, operational efficiency, and customer experience improvements. The position oversees the transformation of complex data into actionable insights using BI reporting, visualization, predictive analytics, automation, and generative AI. It partners across business and technology teams to implement modern analytics solutions and accelerate data-driven decision making.

Requirements

3–5 years of experience in fast-paced, data-driven environments.
Proficiency in Python and SQL.
Experience with cloud platforms such as Azure and Google Cloud.
Ability to translate business problems into analytical and AI-enabled solutions.
Demonstrated success delivering impactful analytics or AI initiatives end-to-end.
Strong analytical methodology and problem-solving skills.
Effective presentation and storytelling skills using PowerPoint and data visualization tools.
Must be a U.S. Citizen or National of the U.S., an alien lawfully admitted for permanent residence, or an alien authorized to work in the U.S. for this employer.

Nice To Haves

Experience with pricing methodologies and revenue management.
Experience implementing or operationalizing AI and machine learning solutions.
Experience with PySpark, Azure Databricks, Google BigQuery, and Vertex AI.
Exposure to neural networks or advanced AI methodologies.

Responsibilities

Define and execute AI-driven BI strategy aligned to enterprise priorities.
Lead teams delivering dashboards, analytics products, and AI-powered insights.
Develop predictive and prescriptive analytics to support business decisions.
Evaluate and implement emerging AI/ML, generative AI, and automation technologies.
Partner with engineering teams to build scalable data pipelines and governed data models.
Ensure data quality, governance, and accessibility across BI platforms.
Translate business needs into analytics and AI use cases for executive stakeholders.
Communicate insights through dashboards, storytelling, and executive presentations.
Collaborate across pricing, revenue management, operations, and technology teams.
Drive automation and continuous improvement initiatives to improve speed-to-insight and business performance.