Entry Level Data Scientist Machine Learning Jobs in Dallas, TX

Why GM Financial 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.

Experience

• 4+ yrs as a Data Scientist or similar quantitative field 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.

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 Ft. Worth, TX 

This position is not open to agency submissions

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About the Role:

The Senior Data Scientist 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.  The Senior Data Scientist is the subject matter expert with an in depth knowledge of quantitative methods and diligent knowledge of data sources and tools.

In this role you will: 

• Provides leadership, coaching, and/or mentoring to Data Scientists I and II
• 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
• 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
• 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
• Comprehensive knowledge and experience with technical systems, datasets, data warehouses, and data analysis techniques
• Efficiently work with large datasets
• Provides leadership, coaching, and/or mentoring to Data Scientists I and II
• 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