AVP Data Science

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 Power Point Efficient  quantitative skills with very large datasets

Provides leadership, coaching and/or mentoring to Data ScientistsMS Office required.

Proficient in at least one of Python, R or SASAbility 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…