Drimva

Veeva Systems

Global Data Science Lead

$120K–$250K

Massachusetts - Boston · Remote · Full-time · Posted Oct 15, 2026

Experience
5+ years of relevant industry experience with a Ph.D., or 8+ years of relevant demonstrable research experience with an equivalent M.S.
Education
Ph.D. in Economics, Machine Learning, Applied Statistics, Applied Mathematics, Physics, Engineering, Computer Science, or another quantitative discipline; or equivalent M.S.

About the job

Leads Veeva’s Global Analytics data science function, translating AI strategy into delivery and overseeing teams and AI solutions for life sciences data.

What you'll do

  • Lead, mentor, and manage data scientists, AI/ML engineers, and analysts; align team priorities and delivery plans with leadership.
  • Own global model methodology, including management, observability, testing, deployment, and responsible AI practices.
  • Oversee advanced analytics, machine learning, and generative AI solutions and infrastructure for customer engagements.

What they ask for

  • Ph.D. in a quantitative discipline with 5+ years of relevant industry experience, or equivalent M.S. with 8+ years of relevant demonstrable research experience.
  • Life Sciences industry experience applying analytics and AI/ML to related datasets.
  • Hands-on experience building or deploying LLM-based systems; advanced specialization in data science and AI techniques.
  • Proven leadership of teams of 10+ people.

Nice to have

  • Advanced experience with AWS, Snowflake, or Databricks.
  • Experience with LLM orchestration frameworks (e.g., LangChain, LlamaIndex), vector databases, or designing AI-native products or workflows.

Pay

USD $120,000 - $250,000 base salary

Tools

AWS, Snowflake, Databricks, LangChain, LlamaIndex, RAG

AI focus

Applies machine learning and generative AI/LLM techniques to life sciences data; leads LLM system development and deployment, AI strategy execution, model governance, and responsible AI practices.

Model-written summary · the original posting is authoritative

First seen Oct 29, 2026 · Last verified Nov 5, 2026 (UTC)