Clarivate Analytics Logo

Clarivate Analytics

Vice President, Data Science

Posted Yesterday
Be an Early Applicant
In-Office or Remote
Hiring Remotely in United States of America
240K-300K Annually
Expert/Leader
In-Office or Remote
Hiring Remotely in United States of America
240K-300K Annually
Expert/Leader
Leads the enterprise Data Science and AI vision, strategy, roadmap, and global organization. Oversees production-grade machine learning, Generative AI, Agentic AI, predictive modeling, AI governance, deployment, monitoring, cost optimization, and responsible AI. Partners with executive, product, engineering, commercial, legal, operations, and customer success stakeholders to deliver scalable AI products, automation, improved customer outcomes, and measurable business value.
The summary above was generated by AI

 

Shape the future of AI in Intellectual Property. As Vice President, Data Science, you will set the vision for our Data Science & AI organization and turn advances in machine learning, Generative AI, and Agentic AI into scalable products, smarter operations, and measurable business value.


This is an opportunity to pair technical ambition with executive leadership—guiding a global, multidisciplinary organization from AI strategy to production-grade solutions. If you have led enterprise-scale AI teams and brought AI solutions into production, we invite you to help define what comes next for our IP business.


About You – experience, education, skills, and accomplishments
  • 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, including 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 of experience defining AI strategy and leading the delivery of production-grade AI/ML systems and data products at enterprise scale.
  • At least 7 years of experience in AI and machine learning, with experience spanning deep learning, NLP, RAG, LLMs, Generative AI, Agentic AI, MLOps, and responsible AI practices.
  • At least 7 years of experience 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 of experience 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 of experience developing or leading AI solutions, including experience with Generative AI, LLMs, SLMs, RAG, multimodal AI, knowledge graphs, prompt engineering, agentic workflows, evaluation, AI safety, and hallucination mitigation.
  • At least 7 years of experience developing or leading AI/ML model development, including experience with pretraining, fine-tuning, PEFT/LoRA, quantization, distillation, explainability, benchmarking, and A/B testing.
  • At least 7 years of experience in AI/ML engineering or production deployment, including experience with deployment pipelines, monitoring, feature stores, vector databases, drift detection, observability, data quality, cloud-native platforms, and Kubernetes.
  • At least 7 years of experience managing AI/ML costs and measuring business value, including experience with LLM cost management, model routing, GPU and inference optimization, hybrid model strategies, FinOps, and AI ROI measurement.
  • At least 7 years of experience presenting AI strategy and outcomes to executives, customers, boards, investors, or industry forums.

It would be great if you also have . . .
  • PhD in Computer Science, Data Science, AI, Statistics, Mathematics, Engineering, Economics, or a related quantitative field.
  • Experience in Intellectual Property, Legal Technology, Information Services, Scientific Research, SaaS, or Knowledge Management industries.
  • Recognized AI/ML contributions through patents, publications, conference talks, or AI Centers of Excellence leadership.
What will you be doing in this role?
  • Define and execute the enterprise data science and AI vision, aligning investment and delivery with business strategy, product innovation, and long-term growth.
  • Differentiate our 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 that improve decisions, customer outcomes, and operational performance.
  • Define the strategy 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, a culture of 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.

About the Team

Our Data Science & AI organization drives innovation and competitive advantage across the IP business through advanced analytics, machine learning, Generative AI, and Agentic AI. The team brings together Data Scientists, Applied Scientists, ML Engineers, MLOps Engineers, and specialists focused on customer insight, workflow automation, product intelligence, and strategic decision-making. We work closely with Product, Engineering, Commercial, Operations, Legal, and Customer Success to turn AI capabilities into business and customer outcomes.


Hours of Work

You will primarily work full-time business hours in your time zone, with flexibility to support global business needs.


Compensation – US only

The expected base salary for this position is $240,000–$300,000 USD per year. This role is eligible for bonus earnings. Individual pay is based upon experience, education, skill and ability, expertise, and relevant factors.


In addition to a competitive remuneration package, you will be eligible to participate in a benefits package that includes medical, dental, prescription drug, life insurance, 401k with match, long term disability coverage, vacation, sick time, volunteer time, discount programs, and many more.


At Clarivate, we are committed to providing equal employment opportunities for all qualified persons with respect to hiring, compensation, promotion, training, and other terms, conditions, and privileges of employment. We comply with applicable laws and regulations governing non-discrimination in all locations.

Similar Jobs

17 Hours Ago
Remote
USA
220K-260K Annually
Expert/Leader
220K-260K Annually
Expert/Leader
Fintech • Payments • Financial Services
Leads enterprise business intelligence, analytics, data science, and AI-assisted analysis strategy. Oversees analytics modernization, predictive modeling, data governance, semantic frameworks, reporting standards, and reliable data access for business users and AI tools. Partners with Product, Engineering, Data Engineering, and AI Enablement teams to deliver governed datasets and analytical capabilities. Builds and develops high-performing analytics and data science teams while communicating strategy, quality, performance, and business outcomes to executives.
Top Skills: Amazon RedshiftAWSData GovernanceMachine LearningPower BIPredictive AnalyticsPythonSemantic LayersSnowflakeSQLTableau
One Month Ago
Remote
United States
285K-350K Annually
Expert/Leader
285K-350K Annually
Expert/Leader
Insurance
Leads the strategy, technical direction, and delivery of insurance data science across pricing, underwriting, cost modeling, demand modeling, and growth. Oversees predictive modeling standards, model lifecycle governance, engineering collaboration, regulatory alignment, and production deployment. Builds and develops a high-performing data science organization while partnering with actuarial, product, underwriting, pricing, and executive leadership to connect analytical work with profitability and business outcomes.
Top Skills: Artificial IntelligenceGlmsGradient BoostingMachine LearningModel MonitoringNeural NetworksSoftware TestingVersion Control
An Hour Ago
Remote or Hybrid
67K-126K Annually
Senior level
67K-126K Annually
Senior level
Artificial Intelligence • Fintech • Insurance • Marketing Tech • Software • Analytics
Investigates and resolves moderate-to-severe property loss claims, determines coverage, coordinates appraisals and vendors, supports policyholders with damage itemization and emergency arrangements, identifies suspicious losses, and recommends SIU referrals. The role requires independent claims management, negotiation, customer service, construction knowledge, advanced property training, licensing eligibility, and may involve catastrophe duty.

What you need to know about the Austin Tech Scene

Austin has a diverse and thriving tech ecosystem thanks to home-grown companies like Dell and major campuses for IBM, AMD and Apple. The state’s flagship university, the University of Texas at Austin, is known for its engineering school, and the city is known for its annual South by Southwest tech and media conference. Austin’s tech scene spans many verticals, but it’s particularly known for hardware, including semiconductors, as well as AI, biotechnology and cloud computing. And its food and music scene, low taxes and favorable climate has made the city a destination for tech workers from across the country.

Key Facts About Austin Tech

  • Number of Tech Workers: 180,500; 13.7% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Dell, IBM, AMD, Apple, Alphabet
  • Key Industries: Artificial intelligence, hardware, cloud computing, software, healthtech
  • Funding Landscape: $4.5 billion in VC funding in 2024 (Pitchbook)
  • Notable Investors: Live Oak Ventures, Austin Ventures, Hinge Capital, Gigafund, KdT Ventures, Next Coast Ventures, Silverton Partners
  • Research Centers and Universities: University of Texas, Southwestern University, Texas State University, Center for Complex Quantum Systems, Oden Institute for Computational Engineering and Sciences, Texas Advanced Computing Center

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account