Principal Data Scientist, Capabilities & Acceleration

What you'll do

• Design and ship production-grade AI capabilities that combine data engineering, applied AI, and analytical judgment.
• Serve as the first builder on shared capabilities to validate architectural decisions through real implementations.
• Design data architecture, semantic grounding, and pipelines that support AI and analytical workloads.
• Establish patterns for governed metric definitions, data quality, and freshness guarantees for downstream products.
• Define production standards for data science work, including testing, observability, cost awareness, and graceful failure.
• Convert one-off data science solutions into reusable, discoverable assets for the broader organization.
• Mentor data scientists on engineering practices, AI-native development, and data architecture.
• Identify and prioritize missing data foundations to eliminate duplicated efforts across the organization.

What we're looking for

• 10+ years of experience across data science, data engineering, or applied machine learning.
• Proven record of shipping production systems rather than analyses alone.
• Demonstrated depth in data architecture and modeling for analytical and AI products.
• Hands-on experience building LLM-based applications, agentic workflows, and evaluation practices.
• Advanced skills in SQL and Python with strong software engineering fundamentals including version control, testing, and CI/CD.
• Practical experience with distributed data processing (e.g., Spark, Databricks), pipeline orchestration, and production deployment.
• Excellent communication skills with a track record of influencing technical direction across teams.
• Familiarity with semantic layers, metric governance, or metadata systems (preferred).