Senior AI Data Science Manager

KeyBank

. Lead, mentor, and develop a team of Data Scientists .

Posted 10/16/2026full-timeBrooklyn • Ohio • United StatesSenior💰 $116,000 - $216,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading and mentoring Data Science teams, with a strong focus on Generative AI techniques, LLM architecture, and ethical AI practices. Capable of managing AI initiatives, establishing evaluation frameworks, and ensuring compliance with regulatory standards.

Highest-signal resume keywords

Generative AI TechniquesLLM ArchitectureTeam LeadershipPython Statistical CodingAI Ethics Principles

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningArtificial IntelligenceData ScienceModel EvaluationStatistical CodingData CurationModel Behavior AnalysisPrompt EngineeringFine-TuningBias Mitigation

Soft Skills

MentoringCommunicationInnovationAccountabilityContinuous Learning

Tools & Technologies

Hugging Face TransformersLangChainOpenAI APIPandasNumPyCloud-Based ComputingDistributed ComputingVector DatabasesMLOps PrinciplesMonitoring Approaches

Certifications & Qualifications

Master's DegreePh.D.

Industry Keywords

Financial Crime Regulatory RequirementsResponsible AI GovernanceData Analysis Best PracticesAI Deployment ComplianceCross-Functional Collaboration

Tech Stack

Tools & technologies

CloudNumpyPandasPython

About the role

Key responsibilities & impact

Lead, mentor, and develop a team of Data Scientists
Set goals, provide technical guidance, and foster innovation, accountability, and continuous learning
Manage team workload, prioritization, and delivery across multiple AI initiatives
Guide prompt and context engineering, retrieval-augmented generation, fine-tuning, model adaptation, experimentation, evaluation, data and ground-truth requirements, and model behavior analysis
Establish and govern internal frameworks for evaluating LLM performance
Define metrics for accuracy, fluency, coherence, factual correctness, toxicity, bias, and safety
Ensure consistent standards for data curation, ground-truth dataset creation, and adversarial testing
Oversee documentation of model configurations, prompt and context strategies, assumptions, evaluation methodologies, behaviors, limitations, and failure modes
Partner with model validation, compliance, technology, and risk teams on safe and ethical AI deployment
Champion RLHF, supervised fine-tuning, prompt and context optimization, and bias and safety mitigation
Translate generative AI concepts, evaluation findings, and risks for technical and non-technical stakeholders
Represent the data science team in cross-functional planning and executive discussions
Build team capability in Generative AI ethics, responsible AI, and LLM-specific risk management
Stay current on emerging technologies and industry best practices

Requirements

What you’ll need

Master's or Ph.D. in a quantitative discipline
At least 7+ years of relevant experience
At least 2+ years of direct people or team leadership
Experience leading data science or AI teams and developing talent
Experience managing delivery, setting technical standards, and guiding cross-functional partners
Deep expertise with traditional Machine Learning/Artificial Intelligence modeling practices
Demonstrated experience with Generative AI techniques
Strong understanding of LLM architecture, lifecycle methods, evaluation approaches, capabilities, and limitations
Hands-on experience with statistical coding in Python
Experience with Hugging Face Transformers, LangChain, OpenAI API, Pandas, and NumPy
Knowledge of traditional databases, cloud-based computing, and distributed computing
Familiarity with vector databases, retrieval systems, knowledge graphs, orchestration patterns, MLOps principles, and monitoring approaches
Knowledge of financial crime regulatory requirements, technology, and data analysis best practices
Strong understanding of AI ethics principles, responsible AI governance frameworks, and regulatory considerations for AI/LLM deployments
Excellent verbal, written, and visual communication skills
Occasional travel, including overnight stays

Benefits

Comp & perks

Eligibility for incentive compensation, which may include production, commission, and/or discretionary incentives
Hybrid work arrangement (3+ days)
Flexible options for roles that can be performed effectively in a mobile environment
Reasonable accommodations for qualified individuals with disabilities or disabled veterans