Digital Analyst II

Why GM Financial Technology

Innovation isn’t just a talking point at GM Financial, it’s how we operate. From generative AI and cloud-native technologies to peer-led learning and hackathons, our tech teams are building real solutions that make a difference. We’re committed to AI-powered transformation, using advanced machine learning and automation to help us reimagine customer interactions and modernize operations, positioning GM Financial as a leader in digital innovation within a dynamic industry.

Join us and discover a workplace where your ideas matter, your development is prioritized, and you can truly make a global impact.

About the role:

Digital Marketing Analyst II is responsible for supporting data-driven decision-making across the enterprise. In this role, you will collaborate with diverse business units and stakeholders to understand their goals, establish key performance indicators (KPIs), and deliver insightful analyses. You will leverage a tool-agnostic approach – utilizing various data platforms (such as SAS, Databricks), programming languages like SQL, Python, and business intelligence tools like Power BI, Tableau– to gather, analyze, and visualize data. From exploratory data analysis and robust reporting to interactive dashboard development and data quality validation, you will play a critical role in transforming complex data into clear, actionable insights that drive strategic business decisions. While descriptive and diagnostic analytics (reporting and trend analysis) are the core focus of this position, you will also assist in predictive and prescriptive analytics projects (including basic modeling and forecasting) as a supporting function to enhance the depth of insights provided to stakeholders.

In this role you will:

• Collaborate with cross-functional stakeholders to understand business needs, define KPIs, and align analytics deliverables with organizational goals. 

• Perform exploratory data analysis using SAS, Databricks, and Python to identify trends, patterns, and insights across enterprise data sources. 

• Design, build, and maintain reports and interactive dashboards in Power BI to track performance and support decision-making. 

• Validate data accuracy and integrity by identifying discrepancies and partnering with technical teams to resolve data quality issues. 

• Translate analytical findings into clear, actionable insights through concise storytelling, presentations, and written summaries. 

• Manage multiple analytics projects simultaneously while adapting to changing priorities and stakeholder requirements.

• Support experimentation and testing (A/B, multivariate, etc.)