Global Data Science Lead

About the role

Veeva's Global Analytics Business Consulting Team applies data science and AI to turn commercial, medical and regulatory data into action. It is seeking a Global Data Science Lead to support the execution of the Data Science AI strategy, leading a group of data scientists, AI/ML engineers and analysts and partnering with Global Analytics leadership to turn strategy into delivery using advanced analytics, machine learning and generative AI/LLM techniques.

Key responsibilities

• Lead the Data Science function within the Global Analytics Team in line with Veeva's Analytics Business Consulting goals
• Lead, mentor and inspire a team of data scientists, AI/ML engineers and analysts
• Partner with Global Analytics leadership to turn the Data Science AI strategy into team priorities and delivery plans
• Own global methodology: model management, observability, testing and deployment
• Foster collaboration between consulting, data science and engineering teams
• Oversee the design and implementation of advanced analytics, machine learning and generative AI/LLM models
• Ensure robust, scalable and efficient data and AI infrastructure
• Translate customer business requirements into AI-native, data-driven solutions and surface AI opportunities with product and business stakeholders
• Enforce best practices for data quality, security, governance and responsible AI use, and implement rigorous testing of models

Required profile

• Ph.D. in Economics, Machine Learning, Applied Statistics, Applied Mathematics, Physics, Engineering, Computer Science or another quantitative discipline with 5+ years of relevant industry experience, or an equivalent M.S. with 8+ years of demonstrable research experience
• Experience applying analytics and AI/ML to Life Sciences data sets
• Proven leadership of teams of 10+ people
• Excellent communication skills and comfort with changing requirements and working with minimal supervision

Required skills

• Hands-on experience building or deploying LLM-based systems (prompt engineering, RAG, agentic workflows, fine-tuning)
• Deep knowledge of classification, pattern recognition, clustering, feature analysis, NLP, fuzzy matching, sentiment analysis, A/B testing and active/adaptive learning
• Nice to have: AWS, Snowflake or Databricks, data pipelines, LLM orchestration frameworks (e.g. LangChain, LlamaIndex) and vector databases

What we offer

• Base pay of $120,000 - $250,000, with possible bonus and/or stock bonus
• Medical, dental, vision and basic life insurance
• Flexible PTO and company-paid holidays
• Retirement programs and a 1% charitable giving program
• Work anywhere option: home or office on any given day