✦ Luna Orbit — AI & Machine Learning

Principal - Data Scientist - Responsible AI

at Ally Financial

Hybrid Posted March 13, 2026
Type Full-Time
Experience mid
Exp. Years 3+ years
Education Not specified
Category AI & Machine Learning

A role supporting enterprise AI initiatives focusing on responsible and generative AI, building and deploying AI solutions that are safe, ethical, and scalable.

  • Lead experimentation initiatives
  • Advance responsible AI practices
  • Develop GenAI workflows
  • Own Responsible AI lifecycle
  • Partner with business and engineering teams

Involves developing machine learning models, generative AI workflows, and responsible AI practices using Python, AI evaluation pipelines, and cloud-based platforms.

The ideal candidate is a mid-level data scientist with 3+ years of experience in AI and machine learning, particularly in responsible and generative AI. They possess strong Python skills and experience with AI model evaluation and bias mitigation, capable of leading AI projects with ethical considerations.

Machine LearningGenerative AIResponsible AIPythonA/B testing
GenAI workflowsPrompt-driven systemsAgent-based solutionsBias detectionAI governance
PythonGenAI platformAI evaluation pipelines
Machine LearningGenerative AIResponsible AIPythonPrompt engineeringModel evaluationBias mitigationData analysisA/B testing
Machine LearningGenerative AIResponsible AIAI systemsPythonPrompt engineeringModel evaluationBias mitigationModel deploymentA/B testingData analysisModel risk management
CollaborationCommunicationProblem-solvingAnalytical thinkingTeamworkEthical judgment
Industry Fintech
Job Function Develop and deploy responsible AI and generative AI solutions
Data ScientistResponsible AIGenerative AIMachine LearningAI systemsPythonA/B testingModel deploymentBias mitigationAI governancePrompt-driven systemsModel evaluationData analysisModel risk managementAI/ML

Lack of experience in Responsible AI or Generative AI, No Python programming skills, No experience with AI model evaluation or bias mitigation, Unwillingness to work in a hybrid environment

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