Avp Data Warehouse Jobs (NOW HIRING)

Why GM Financial?

GM Financial is the wholly owned captive finance subsidiary of General Motors and is 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 our long-standing relationships with auto dealers, we offer attractive retail financing and lease programs to meet the needs of each customer. We also offer commercial lending products to dealers to help them 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. Here we do more than work - we thrive.

Our Purpose: We pioneer the innovations that move and connect people to what matters

The AVP of Data Science leads a team of data scientists in developing advanced analytics, machine learning models, and data-driven solutions that support strategic business objectives. This role oversees research initiatives, guides the application of analytics to complex business challenges, and delivers actionable insights that drive operational improvements and informed decision-making.

The AVP partners closely with business leaders to identify opportunities, communicate analytical findings, and ensure data science solutions deliver measurable value. This position combines technical leadership, people management, and strong business acumen to advance the organization's analytics capabilities and outcomes.

What makes You an ideal candidate?

• Strong quantitative, analytical and data interpretation skills with a solid foundation of mathematics, probability and statistics
• Ability to identify and understand business issues and map these issues into quantitative questions
• Comprehensive knowledge and experience with technical systems, datasets, data warehouses and data analysis techniques
• Proficiency in experimental design, ability to design and implement documentation and monitoring protocols
• Advanced knowledge of principles, standards, practices and techniques relating to quantitative analysis for a financial firm
• Advanced knowledge and demonstrated understanding of applied methodologies including least squares regression, logistic regression, sampling methodologies, time series, survival analysis, cluster analysis, categorical data analysis, decision trees, multivariate methodologies, non-parametric techniques, principal components and linear programming techniques.
• Advanced skills in Python, SAS, SQL, R, JMP, Excel, Word and PowerPoint
• Efficient quantitative skills with very large datasets
• Provides leadership, coaching and/or mentoring to Data Scientists
• MS Office required.
• Proficient in at least one of Python, R or SAS
• Ability to lead technical professional and influence their technical and leadership development.
• Strong written and verbal presentation skills with an ability to communicate effectively with senior management by making complex concepts easy to understand
• Ability to be curious, ask questions, explore and be creative when analyzing data and business problems
• Ability to identify and seek needed information/research skills.
• Analytical thinking skills
• Ability to interact collaboratively with internal and external customers
• Capable of managing multiple and varied projects, including the ability to coordinate and balance numerous tasks in a time-sensitive environment, under pressure
• Strong problem-solving skills
• Extensive experience presenting highly complex analysis to upper management is required
• Normal office environment

Additional Knowledge and Skills

• Working effectively within an AI enabled environment:  
• 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 

Work Experience and Education

• 7-10 years experience in modeling Req
• 3-5 years experience in management and/or leadership Req
• Bachelor's Degree Required
• Master's Degree PhD in Statistics, Applied Mathematics, Econometrics, Economics, Operations Research, Industrial Engineering, Physics, Computer Science or similar quantitative field. 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, 3-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-WB1

About this role:

• Manage a team of Data Scientists
• Lead in conducting research projects, incorporate project design, data collection and analysis, summarizing findings, developing recommendations and effectively communicating to leadership the impact to the Business.
• Build technical knowledge to support research and analytic responsibilities including advanced techniques and algorithms.
• Develop and applies algorithms or models to key business metrics with the goal of improving operations or answering business questions.
• Present findings and analysis for use in decision-making.
• Ensure that the delivered products meet the business needs of the Company.
• Partner with and provide recommendations to business leadership on the appropriate application of analytics to business strategies and effectively communicate analysis and implications to senior leadership.
• Prioritize tasks and meets project deadlines in a fast-paced work environment.