Job Description

This position will be posted until filled.

Responsibilities

About the Role

The Data Scientist II is responsible for implementing the design, development, deployment, and maintenance of predictive/prescriptive/statistical models in originations, collections, risk, pricing, fraud, customer experience and marketing. Modeling with expertise in forecasting, optimization, data mining, analysis, and analyzing complex datasets; Conducting studies with the use of descriptive and supervised machine learning methods and advanced statistical methods using innovative and the latest advanced technique and algorithms; Summarizing, reporting, and providing polished presentations of findings to a variety of internal clients as well as working with other departments to achieve the overall company objectives; Lead in the production of research and analysis to quantify the impact of internal and external environments on portfolio performance.

In this role you will:

• Performs research, analysis, and modeling on organizational data
• Assists in analyzing key metrics and performing data analysis
• Builds technical knowledge to support research and analytic responsibilities including advanced techniques and algorithms
• Conducts research projects, incorporate project design, data collection and analysis, summarizing findings, developing recommendations and effectively communicating to leadership the impact to the business
• Develops and applies algorithms or models to key business metrics with the goal of improving operations or answering business questions
• Presents findings and analysis for use in decision making
• Ensures that the delivered products meet the business needs of the company
• Partners 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
• Prioritizes tasks and meets project deadlines in a fast paced work environment.

Qualifications

What makes You an ideal candidate?

• Ability to identify and understand business issues and map these issues into quantitative questions
• 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, PowerPoint
• Ability to design and implement model documentation and monitoring protocols
• Demonstrated understanding and experience with technical systems, datasets, data warehouses, and data analysis techniques
• Efficiently work with large datasets
• Strong quantitative, analytical and data interpretation skills with a solid foundation of mathematics, probability, and statistics
• 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

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 & Education

• 2-4 years as Data Scientist or similar quantitative field required
• High School Diploma or equivalent required
• Master's Degree or PhD in Statistics, Applied Mathematics, Econometrics, Economics, Operations Research, Industrial Engineering, Computer Science, Physics or similar quantitative field required (a combination of education, certifications, and/or work experience may be considered in lieu of an advanced degree)

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.

Compensation: Competitive pay and bonus eligibility.

Work Life Balance: Flexible hybrid work environment, 2-days a week in office.

This position is not open to agency submissions

#GMFJobs #LI-Hybrid #LI-SC1