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Data Science Manager
GM Financial. Lead development, deployment, and maintenance of predictive, prescriptive, and statistical models across originations, collections, risk, pricing, fraud, customer experience, and marketing .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates advanced quantitative and analytical skills in machine learning, statistical modeling, and predictive analytics, with a strong emphasis on technical leadership and mentorship in data science. Capable of designing and implementing innovative algorithms and models to drive strategic business decisions and improve operational efficiency.
Highest-signal resume keywords
Machine LearningPredictive ModelingPythonStatistical AnalysisProject Leadership
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
Statistical ModelingRegression AnalysisTime Series AnalysisClusteringDecision TreesOptimizationSimulationDimensionality ReductionData MiningPredictive Analytics
Soft Skills
Technical LeadershipMentoringCollaborationPresentation SkillsIndependent Research
Tools & Technologies
PythonSASSQLRJMPTensorFlowKerasAzure DevOpsMicrosoft OfficeAI Tools
Certifications & Qualifications
Master’s DegreePhD in StatisticsPhD in Applied MathematicsPhD in EconometricsPhD in EconomicsPhD in Operations ResearchPhD in Industrial EngineeringPhD in PhysicsPhD in Computer Science
Industry Keywords
Data SciencePredictive AnalyticsMachine Learning SolutionsBig Data PlatformsData WarehousesData LakesAgile MethodologiesLean DevelopmentResponsible AIData Protection
Tech Stack
Tools & technologiesAzureKerasPythonSQLTensorflow
About the role
Key responsibilities & impact- Lead development, deployment, and maintenance of predictive, prescriptive, and statistical models across originations, collections, risk, pricing, fraud, customer experience, and marketing
- Provide technical leadership and mentorship to Data Scientists
- Apply advanced machine learning, statistical, forecasting, optimization, and data mining techniques to complex business problems
- Lead research, analysis, and modeling to quantify impacts on portfolio performance and key business metrics
- Design and execute studies using descriptive analytics, supervised machine learning, and advanced statistical methodologies
- Develop innovative algorithms and models to improve operations and support decision-making
- Coordinate project activities and provide technical oversight
- Partner with business leaders to identify analytics opportunities and provide strategic recommendations
- Present analytical findings and recommendations to stakeholders and senior leadership
- Lead research initiatives from project design and data collection through analysis, recommendations, and implementation
- Provide leadership, coaching, mentoring, and technical training to Data Scientists
- Prioritize multiple initiatives and deliver high-quality work in a fast-paced environment
Requirements
What you’ll need- Advanced quantitative and analytical skills grounded in mathematics, probability, statistics, machine learning, and predictive modeling
- Deep knowledge of regression, time series analysis, survival analysis, clustering, decision trees, optimization, simulation, dimensionality reduction, and other advanced analytical methods
- Strong experience with Python, SAS, SQL, R, JMP, and Microsoft Office applications
- Preference for experience with TensorFlow and Keras
- Experience designing, deploying, documenting, monitoring, and maintaining analytical models and machine learning solutions
- Experience with DevOps/MLOps practices and Azure DevOps environments
- Knowledge of data warehouses, data lakes, big data platforms, and large-scale dataset analysis
- Strong written, verbal, and presentation skills
- Ability to conduct independent research and develop innovative solutions
- Ability to build collaborative relationships and partner with technical teams, business stakeholders, and leadership
- Experience leading multiple projects and mentoring others
- Familiarity with Agile, Lean Development, and structured problem-solving methodologies
- Ability to use AI tools such as Microsoft Copilot
- Ability to evaluate AI outputs for accuracy, compliance, and bias
- Experience integrating AI into workflows
- Familiarity with AI-assisted research, summarization, and content generation
- Understanding of responsible AI use, ethics, and data protection
- 5+ years as a Data Scientist or in a similar quantitative field required
- 1+ years in a project leadership role required
- Master’s Degree or PhD in Statistics, Applied Mathematics, Econometrics, Economics, Operations Research, Industrial Engineering, Physics, Computer Science, or a similar quantitative field required
Benefits
Comp & perks- 401K matching
- Bonding leave for new parents: 12 weeks, 100% paid
- Tuition assistance
- Training
- GM employee auto discount
- Community service pay
- Nine company holidays
- Competitive pay and bonus eligibility
- Flexible hybrid work environment