Vice President, Data Science

Clarivate

. Define and execute the enterprise data science and AI vision aligned with business strategy, product innovation, and long-term growth .

Posted 11/5/2026full-timeAlexandria • Virginia • United StatesLead💰 $240,000 - $300,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining and executing enterprise data science and AI strategies, with a strong focus on Generative AI, machine learning, and advanced analytics. Proven ability to lead global teams, manage AI/ML solutions, and align technical strategies with business objectives.

Highest-signal resume keywords

AI Strategy DevelopmentGenerative AI SolutionsPredictive ModelingTeam LeadershipAI Governance and Compliance

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningNatural Language ProcessingGenerative AIPredictive ModelingReinforcement LearningModel Fine-TuningData Quality ManagementCloud-Native PlatformsKubernetes

Soft Skills

Stakeholder CommunicationTeam BuildingStrategic ThinkingInnovationAccountability

Tools & Technologies

AI PlatformsData Analytics ToolsMonitoring SystemsFeature StoresVector Databases

Industry Keywords

Data ScienceAI EthicsResponsible AIAI ROI MeasurementEnterprise Data Governance

Tech Stack

Tools & technologies

CloudKubernetes

About the role

Key responsibilities & impact

Define and execute the enterprise data science and AI vision aligned with business strategy, product innovation, and long-term growth
Differentiate products, operations, and customer experiences through AI
Create a multi-year roadmap for machine learning, Generative AI, Agentic AI, and advanced analytics adoption
Lead the strategy, architecture, and implementation of Generative AI and Agentic AI solutions across the business
Build scalable AI agents, copilots, assistants, reasoning systems, and workflow automation capabilities
Set standards for prompt engineering, context management, retrieval, orchestration, and agent evaluation
Lead predictive modeling, recommendation systems, forecasting, analytics platforms, and reusable AI capabilities
Translate business opportunities into scalable AI solutions improving decisions, customer outcomes, and operational performance
Define strategies for foundation model selection, fine-tuning, deployment, benchmarking, governance, lifecycle management, and cost optimization
Evaluate responsible uses of proprietary enterprise data and open-source and commercial model ecosystems
Establish enterprise standards for responsible AI, governance, transparency, security, compliance, explainability, monitoring, and risk mitigation
Build, lead, and develop a global Data Science & AI organization with technical excellence, talent depth, innovation, and accountability for business impact
Partner with Product, Engineering, Commercial, Operations, Legal, Customer Success, and executive stakeholders to align AI capabilities with business priorities and communicate technical strategy
Establish KPIs for AI adoption, model performance, ROI, productivity, customer impact, cost efficiency, and delivery of high-value initiatives

Requirements

What you’ll need

Bachelor’s or master’s degree in Computer Science, Data Science, AI, Statistics, Mathematics, Engineering, Economics, or a related quantitative field
15+ years of progressive experience in Data Science, AI, Machine Learning, Advanced Analytics, or related fields
8+ years leading enterprise-scale global teams
Experience managing Data Scientists, Applied Scientists, AI Researchers, ML Engineers, Data Engineers, and MLOps professionals
At least 7 years defining AI strategy and leading production-grade AI/ML systems and data products at enterprise scale
At least 7 years in AI and machine learning spanning deep learning, NLP, RAG, LLMs, Generative AI, Agentic AI, MLOps, and responsible AI practices
At least 7 years presenting AI or machine learning technical strategy to executive stakeholders and partnering with Product, Engineering, Commercial, Operations, Legal, and Customer Success teams
At least 7 years developing or leading AI/ML solutions involving predictive modeling, deep learning, NLP, recommendation systems, forecasting, computer vision, graph methods, or experimentation
At least 7 years developing or leading AI solutions involving Generative AI, LLMs, SLMs, RAG, multimodal AI, knowledge graphs, prompt engineering, agentic workflows, evaluation, AI safety, and hallucination mitigation
At least 7 years developing or leading AI/ML model development involving pretraining, fine-tuning, PEFT/LoRA, quantization, distillation, explainability, benchmarking, and A/B testing
At least 7 years in AI/ML engineering or production deployment involving deployment pipelines, monitoring, feature stores, vector databases, drift detection, observability, data quality, cloud-native platforms, and Kubernetes
At least 7 years managing AI/ML costs and measuring business value, including LLM cost management, model routing, GPU and inference optimization, hybrid model strategies, FinOps, and AI ROI measurement
At least 7 years presenting AI strategy and outcomes to executives, customers, boards, investors, or industry forums

Benefits

Comp & perks

Bonus earnings eligibility
Medical insurance
Dental insurance
Prescription drug coverage
Life insurance
401(k) with match
Long-term disability coverage
Vacation
Sick time
Volunteer time
Discount programs