Senior Director, Data Science and AI – Services

Cushman & Wakefield

Senior Director, Data Science & AI responsible for executing AI strategy and leading a multidisciplinary team. Driving innovation and developing AI solutions while ensuring governance and operational standards.

Posted 7/29/2026full-timeRemote • 🇺🇸 United StatesSenior💰 $204,000 - $240,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading the architecture, development, and deployment of AI solutions, with a strong focus on generative AI, MLOps, and agentic systems. Proven ability to manage teams, establish governance frameworks, and optimize AI/ML infrastructure for enterprise-scale applications.

Highest-signal resume keywords

AI Solution ArchitectureGenerative AI ExperienceMLOps/LLMOps PracticesPeople LeadershipAI Governance Frameworks

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningData PreprocessingFeature EngineeringModel SelectionHyperparameter TuningModel MonitoringPrompt EngineeringAgentic AI SystemsAI Risk ManagementModel Versioning

Soft Skills

Team DevelopmentCollaborationInnovation ChampionCulture of ExperimentationCommunication

Tools & Technologies

Cloud AI/ML PlatformsData PipelinesModel Registry ManagementExperiment Tracking

Industry Keywords

AI/ML EngineeringData ScienceEnterprise ScaleResponsible AIData Privacy

Tech Stack

Tools & technologies

Cloud

About the role

Key responsibilities & impact

Lead the end-to-end architecture, development, and deployment of AI solutions including machine learning, GenAI, and Agentic models
Drive the development of agentic AI systems for automated complex workflows
Establish model development standards encompassing data preprocessing, feature engineering, model selection, hyperparameter tuning, evaluation, and documentation
Partner with data engineering teams for scalable and high-quality data pipelines
Mature the organization's AIOps (MLOps & LLMOps) capabilities
Define and enforce standards for model versioning, experiment tracking, reproducibility, and model registry management
Implement robust model monitoring frameworks
Manage cloud AI/ML platform costs and optimize infrastructure utilization
Serve as an internal AI innovation champion
Build and maintain an enterprise AI roadmap
Foster a culture of experimentation through structured ideation programs
Collaborate with product and technology leadership to embed AI capabilities into products
Partner, support, and execute the organization's AI governance framework
Lead AI risk assessments and manage data privacy obligations
Recruit, develop, and retain a high-performing team of AI practitioners

Requirements

What you’ll need

Bachelor's degree in a quantitative field (Finance, Economics, Mathematics, Engineering, Computer Science, etc.) or a bachelor’s degree with related applied quantitative experience
Master's degree in quantitative, arts, or business field preferred
6-8 years of progressive experience in data science, AI/ML engineering & data
1+ years of experience with generative AI and Agentic systems
at least 4+ years in a people leadership role
Demonstrated track record of delivering production AI/ML systems at enterprise scale
Hands-on experience with generative AI, large language models, and prompt engineering in an enterprise context
Experience building or scaling agentic AI systems
Proven experience establishing MLOps/LLMOps practices
Background in AI governance, model risk management, or responsible AI frameworks is highly desirable.

Benefits

Comp & perks

health, vision, and dental insurance
flexible spending accounts
health savings accounts
retirement savings plans
life and disability insurance programs
paid and unpaid time away from work