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Overview

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.

Overview

The Manager Data Scientist is the subject matter expert with an in depth knowledge of quantitative methods and diligent knowledge of data sources and tools. The Manager Data Science brings a strong ability for independent learning and is therefore regarded as a technical expert in the latest advances in Data Science. Responsibilities include: 1. Leading development and deployment of Data Science projects by advising Data Scientists on technical matters2. Guiding Data Scientists in problem formulation3. Ensuring that Data Scientists adhere to Data Science processes such as intake process, version control, and other process-related matters4. Leading execution of deployment strategies5. Leading the implementation of design, development, deployment, and maintenance of predictive/prescriptive/statistical models in originations, collections, risk, pricing, fraud, customer experience and marketing.6. Modeling with expertise in forecasting, optimization, data mining, analysis, and analyzing complex datasets 7. Initiating and guiding studies with the use of descriptive and supervised machine learning methods and advanced statistical methods using innovative and the latest advanced technique and algorithms8. 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 objectives9. Leading in the production of research and analysis to quantify the impact of internal and external environments on portfolio performance

Responsibilities

What makes you an ideal candidate?

  • Provides leadership, coaching, and/or mentoring to Data Scientists I, II, and Senior Data Scientists
  • Coordinates project activities and provide technical oversight
  • Performs and leads 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
  • Develops, leads, and facilitates technical training sessions
  • Perform other duties as assigned
  • Conform with all company policies and procedures
  • Advanced quantitative, analytical and data interpretation skills with a solid foundation of mathematics, probability, statistics, and overall Machine Learning techniques
  • Ability to identify and understand business issues, lead problem formulation, and map these issues into quantitative questions while monetizing business benefits
  • 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, optimization, simulation, and Machine Learning techniques
  • Advanced skills in Python, SAS, SQL, R, JMP, Excel, Word, PowerPoint Knowledge of Python frameworks such as TensorFlow and Keras
  • Ability to design and implement model documentation and monitoring protocols, including deployment and MLOps frameworks Knowledge of Azure DevOps highly desirable
  • Comprehensive knowledge and experience with technical systems, datasets, data warehouses, data lake, and data analysis techniques
  • Efficiently work with large datasets in a big data environment such as Hadoop
  • MS Office required
  • DevOps and MLOps knowledge
  • Proficient in Python or SAS required with a strong preference for Python frameworks
  • Strong written and verbal presentation skills with an ability to communicate effectively with Senior Management by making complex concepts easy to understand This includes knowledge in the design of dashboards
  • Ability to be curious, ask questions, explore, and be creative when analyzing data and business problems
  • Ability to challenge status quo in a positive manner
  • Ability to identify and seek needed information/research skills
  • Analytical and critical thinking skills
  • Ability to interact collaboratively with internal and external customers Ability to build strong relationships
  • Capable of managing and advising others on how to handle multiple and varied projects, including the ability to coordinate and balance numerous tasks in a time-sensitive environment, under pressure
  • Proven problem solving skills, including interviewing, Lean Development, Agile, appreciative inquiry, and ladder of inference

Qualifications

Education

  • Bachelor’s Degree in Statistics, Applied Mathematics, Econometrics, Economics, Operations Research, Industrial Engineering, Physics, Computer Science, or similar quantitative field required
  • Master’s Degree or PhD in Statistics, Applied Mathematics, Econometrics, Economics, Operations Research, Industrial Engineering, Physics, Computer Science, or similar quantitative field required

Experience

  • 5+ years as a Data Scientist or similar quantitative field required
  • 1+ years in a project leadership role required

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To learn more about GM Financial benefits, click here

GM Financial is an Equal Opportunity Employer and is committed to diversity and inclusion at every level of our organization. We do not discriminate against any applicant or employee based on race, color, age, gender, national origin, religion, sexual orientation, gender identity, veteran status, disability or any other federal, state or local protected class.

GM Financial has an accommodation process in place and provides accommodations for applicants and employees with disabilities. If you require a reasonable accommodation because of a disability, please contact Human Resources at 1-866-411-4748 or by e-mail at HRConnection@gmfinancial.com.

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Confirmed 3 hours ago. Posted 30+ days ago.

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