Data Analyst II

GM Financial is the wholly owned captive finance subsidiary of General Motors, headquartered in Fort Worth, U.S. We are a global provider of auto finance solutions, with operations in North America, South America, and the Asia Pacific region. Through long-standing relationships with auto dealers, we offer attractive retail financing and lease programs, as well as commercial lending products to help dealers finance and grow their businesses.

At GM Financial, our team members define and shape our culture—an environment that welcomes new ideas, fosters integrity, and creates a sense of community and belonging.

About the role

The Data Analyst II is responsible for collecting, analyzing, and interpreting data to support business performance, portfolio management, and strategic decision-making within Fleet Solutions. This role leverages advanced analytical techniques to identify trends, mitigate operational and financial risks, improve data quality, and uncover opportunities to enhance fleet utilization, vehicle lifecycle management, customer experience, and profitability.

The analyst partners closely with cross-functional teams, including Fleet Operations, Servicing, Finance, Sales, Customer Experience, and IT, to develop scalable data solutions, automate reporting processes, and deliver actionable business intelligence. The position transforms complex data into meaningful insights through dashboards, visualizations, and performance reporting that support both day-to-day operations and long-term strategic initiatives. This role may also contribute to forecasting, predictive modeling, and scenario analysis related to vehicle demand, maintenance trends, asset utilization, remarketing performance, and operational efficiency.

The Data Analyst II serves as a trusted business partner, providing analytical expertise and recommendations that drive informed decisions, support continuous improvement, and help achieve Fleet Solutions' operational and financial objectives.

Responsibilities

• Develop, maintain, and optimize reports, dashboards, and analytical solutions that provide actionable business insights and support operational and strategic decision-making.
• Partner with business stakeholders, IT, and cross-functional teams to understand business requirements, translate them into analytical solutions, and deliver high-quality reporting products.
• Perform complex data analysis using multiple structured and unstructured data sources to identify trends, risks, opportunities, and process improvement recommendations.
• Validate data accuracy, investigate data quality issues, and collaborate with technical teams to resolve inconsistencies while improving long-term data integrity.
• Create and maintain meaningful business metrics, KPIs, and documentation to support portfolio performance monitoring and operational reporting.
• Present analytical findings and recommendations to business partners and leadership using clear visualizations and concise business storytelling.
• Contribute to the design, enhancement, and automation of reporting processes to improve efficiency, scalability, and data accessibility.
• Provide guidance and knowledge sharing to junior analysts while promoting analytics best practices, documentation standards, and continuous improvement.

Qualifications

• Leverage Power BI and Databricks to build, maintain, and optimize dashboards and reports that clearly communicate business performance, trends, risks, and opportunities to operational and senior leadership audiences.
• Use Databricks to explore, query, transform, and validate large datasets from multiple sources, producing reliable analytical datasets for reporting and decision support.
• Write and troubleshoot SQL to extract, join, aggregate, and reconcile complex data while ensuring results are accurate, complete, and aligned with defined business rules.
• Develop effective Power BI data models, including relationships, calculated columns, measures, and reusable DAX logic that supports consistent and scalable reporting.
• Translate business questions into clearly defined metrics, KPIs, analytical requirements, and reporting solutions, challenging vague or incomplete requests when necessary.
• Apply data visualization and dashboard design best practices to create reports that are intuitive, focused, and actionable rather than simply displaying available data.
• Investigate data discrepancies by tracing issues through source systems, Databricks datasets, transformation logic, and Power BI models, then partner with IT and business teams to resolve root causes.
• Analyze portfolio and operational data to identify meaningful trends, performance drivers, emerging risks, and improvement opportunities, then convert findings into practical recommendations.
• Validate reports and analytical outputs through data reconciliation, reasonableness testing, peer review, and documented quality-control processes before delivery to stakeholders.
• Communicate complex analytical findings in clear business language through written summaries, presentations, and stakeholder discussions, tailoring the level of detail to the audience.
• Manage multiple reporting and analytical priorities by clarifying scope, estimating effort, documenting dependencies, and communicating risks or delays before deadlines are missed.
• Create and maintain documentation for business definitions, data sources, transformation logic, Power BI measures, report functionality, and recurring processes so solutions can be supported and reused by others.
• Partner effectively with business stakeholders, IT teams, data engineers, and other analysts to move work from initial request through requirements, development, testing, implementation, and ongoing support.
• Demonstrate working knowledge of consumer finance, lending, leasing, portfolio performance, or related financial-services concepts, and apply that knowledge when interpreting data and evaluating business impact.
• Support less experienced analysts by reviewing work, sharing Power BI and Databricks best practices, explaining analytical approaches, and helping troubleshoot data or reporting issues.

Skills

• 2-4 years of data mining and query tool experience
• 2-4 years of experience in auto finance (preferred)
• 2-4 years of experience in a similar role (preferred)
• Bachelor’s Degree in Economics, Mathematics, Business Analytics, Computer Science, Statistics, or other quantitative field (or equivalent work experience)
• Master’s Degree in Economics, Mathematics, Business Analytics, Computer Science, Statistics, or other quantitative field (preferred)

Benefits

• 401K matching
• 12 weeks of bonding leave for new parents (100% paid)
• Tuition assistance
• Training opportunities
• GM employee auto discount
• Community service pay
• Nine company holidays

Pay

Competitive pay and bonus eligibility.

Schedule

Hybrid work environment, 2 days a week in office.