Data Analyst II-Credit Review

Why GMF 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. This position will be posted until filled. What makes You an ideal candidate? Understanding of the auto finance industry, including funding and/or underwriting of originations Working knowledge of finance Working knowledge of accounting Working knowledge of consumer credit Working knowledge of statistics Competency with Microsoft Office, focusing on Excel Competency with data visualization tools, including Power BI Knowledge of Provenir, Auto IMS, SalesForce, CPW Ability to plan, execute, and improve work processes to ensure achievement of business objectives Ability to understand GM Financial's business, apply knowledge and critical thinking skills in day-to-day problems and solutions Competency using SAS including basic data functions, macros, SQL and DDE Knowledge of company policies and procedures Excellent interpersonal skills Excellent verbal, written, and communication skills Ability to use appropriate analysis, judgment, and logic when solving issues Detail oriented Ability to coach, lead, motivate, and influence others to support departmental goals and objectives Ability to proactively achieve goals and objectives that positively impact GM Financial's overall business results Ability to work discreetly with confidential information and situations Able to supervise multiple tasks with minimal supervision and be self-motivated Strong problem-solving skills Ability to provide recommendations and make decisions Education & Work Experience Bachelor's Degree Computer Science, Finance, Mathematics, Statistics, Economics, in related field or equivalent work experience in financial analysis, data mining, or loan portfolio analysis required 2-4 years of relevant experience required

What We Offer :

Generous benefits package available on day one to include: 401K matching, bonding leave for new parents (12 weeks, 100% paid), tuition assistance, training, GM employee auto discount, community service pay and nine company holidays.

Our Culture:

Our team members define and shape our culture — an environment that welcomes innovative ideas, fosters integrity, and creates a sense of community and belonging. Here we do more than work — we thrive.

Compensation:

Competitive pay and bonus eligibility.

Work Life Balance:

Flexible hybrid work environment, 2-days a week in office.

NOTE:

We are unable to consider candidates who require visa sponsorship for this position This position is not open to agency submissions #GMFJobs #LI-Hybrid #LI-MO1 About the role The Data Analyst II supports the Credit Review department by utilizing technical expertise to develop new and enhance existing reporting, prepare monthly reports, and extract and analyze data in support of Credit Review's mission. This team member will serve as a technical expert for the department and will collaborate in designing reporting and ad hoc analysis to meet the needs of the department. In this role you will Develop SAS programs to generate datasets, tables, summaries and analysis utilizing multiple data sources, including an Oracle Data Warehouse Collaborate with departmental managers to design, create and implement process and reporting solutions Convert complex data into usable information using appropriate charts, tables and graphs to communicate results to management Respond to ad hoc requests for data and reports Utilize appropriate controls and processes to ensure accuracy and completeness of work Provide direction, training, and guidance to less experienced Data Analysts and lead projects or special assignments as required