About this role
Lead Data Scientist/Statistician at GM driving product safety analytics with a focus on scalable data solutions, AI/ML, and executive-level storytelling. The role blends statistics, data engineering, and leadership to monitor safety issues and enable data-driven decisions.
Key Responsibilities
- Develop and standardize safety analytics practices
- Lead scalable data solutions for safety monitoring
- Build AI/Generative AI capabilities for safety insights
- Communicate results to executive leadership
- Mentor data science team
Technical Overview
Stack includes Python, R, Java, PySpark; ML frameworks (PyTorch, TensorFlow, Scikit-learn); LangChain; SQL; Databricks; data pipelines; time series analyses; anomaly/diagnostics/prognostics; large-scale analytics; vehicle safety domain knowledge
Ideal Candidate
The ideal candidate is a senior data science leader with 8+ years in statistics, AI/ML, and data analytics, holding a Master's in a quantitative field. They excel at building scalable data products, mentoring teams, and communicating complex results to executives, with strong knowledge of GM data ecosystems and cloud data infrastructure.
Must-Have Skills
8+ years of work experience in applied statisticsAI/MLengineeringdata scienceor a related fieldMS in StatisticsMathematicsEconometricsOperations Researchor other relevant degreeStrong background in statistical data analyses (reliability analysisANOVAtime seriescategorical datamultivariate analysissampling design)Strong background in anomaly detectiondiagnostics and prognosticsroot cause analysisExperience in large-scale data analyticsProgramming & Frameworks: PythonRJavaPySparkPyTorchTensorFlowScikit-learnLangChainSQLML & AI: LLMsGenerative AIRAGReinforcement LearningNLPDecision TreesClusteringData Engineering: DatabricksSQLData PipelinesData Preprocessing & Feature EngineeringEffective communication to executive leadershipUnderstanding of vehicle safety technologies
Nice-to-Have Skills
Ph.D. in a quantitative discipline10+ years of work experience in applied statisticsAI/MLengineeringdata scienceDeep knowledge of GM's Data EcosystemDeep knowledge of GM's Cloud Technology Stack for Data ScienceNLP solutions from problem to deploymentProduction deployments of generative AI with business value
Tools & Platforms
DatabricksSQLPythonPySparkLangChain
Required Skills
8+ years in applied statistics AI/ML data science; MS in quantitative discipline; statistical analyses; anomaly detection; diagnostics; prognostics; large-scale data analytics; Python; R; Java; PySpark; PyTorch; TensorFlow; Scikit-learn; LangChain; SQL; LLMs; Generative AI; RAG; Reinforcement Learning; NLP; Decision Trees; Clustering; Databricks; Data Pipelines; Data Preprocessing; Feature Engineering; Time Series; Reliability Analysis
Hard Skills
PythonRJavaPySparkPyTorchTensorFlowScikit-learnLangChainSQLLLMsGenerative AIRAGReinforcement LearningNLPDecision TreesClusteringDatabricksData PipelinesData PreprocessingFeature EngineeringTime SeriesReliability AnalysisAnomaly DetectionDiagnosticsPrognostics
Soft Skills
communicationpresentationleadershipteam collaborationbusiness acumendata storytelling
Keywords for Your Resume
data scientiststatistician leadlead data scientistpythonrsqlpysparknlpllmsgenerative airagreinforcement learningdata pipelinesdatabrickstime seriesanomaly detectionreliability analysisdata modelingdata analyticsai infrastructurePythonSQLDatabricksPysparkLLMsGenerative AINLPReinforcement LearningData PipelinesTime Series
Deal Breakers
8+ years required experience not met, Lack of MS in quantitative discipline, No experience with large-scale data analytics, No experience with LLMs/Generative AI or anomaly diagnostics, Ill-suited for hybrid work setup
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