Digital Analyst II

JOB DESCRIPTION

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.

RESPONSIBILITIES

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.)

• Proficiency in data analysis using SAS, Python, SQL, and large-scale data platforms such as Databricks.
• Experience building reports and interactive dashboards using Power BI or comparable business intelligence tools.
• Strong understanding of data validation, data quality management, and consistent KPI definitions.
• Ability to translate complex analyses into clear, actionable insights through effective data storytelling.
• Strong critical thinking and problem-solving skills that connect analytical results to business decisions.
• Effective written and verbal communication skills with the ability to engage stakeholders at varying levels of data literacy.
• Ability to manage multiple priorities in a fast-paced, cross-functional environment.

• 3-5 years of relevant professional experience in data analytics, business intelligence, or a related analytical role required.
• 2-4 years of hands-on experience using analytics tools and technologies such as SAS, Python, Databricks, and Power BI required.
• Demonstrated experience supporting cross-functional stakeholders with data analysis, reporting, and decision support.
• High School Diploma or equivalent required
• Bachelor's Degree in Marketing, Economics, Business Administration, Statistics, or other quantitative discipline; or equivalent work experience required
• Master's Degree in a quantitative discipline preferred

• Ability to use AI tools (e.g., Microsoft Copilot) to support daily work
• Skills in evaluating AI outputs for accuracy, compliance, and bias
• Experience integrating AI into workflows to improve efficiency or insights
• Familiarity with AI assisted research, summarization, and content generation
• Understanding of responsible AI use, including ethics and data protection

• Experience with AI assisted software development or automation
• Knowledge of prompting techniques to improve output quality
• Awareness of emerging GenAI capabilities and limitations