Sr Principal Data Scientist

Responsibilities

• Set the technical direction for applied ML and agentic AI across the customer lifecycle to drive growth, monetization, and retention.
• Architect systems for AI sub-agents, focusing on evidence grounding, risk calibration, decision evaluation, and safety at scale.
• Define modeling, evaluation, and experimentation standards, including offline metrics, online rollouts, and production monitoring.
• Personally develop and ship high-leverage models and sub-agents to de-risk complex approaches.
• Drive technical decisions regarding data foundations and the knowledge layers used for agentic reasoning.
• Partner with senior Product, Engineering, and Applied AI leaders to shape the organizational strategy and roadmap.
• Mentor staff and principal data scientists, review technical designs, and raise the bar for modeling rigor across the team.

Requirements

• Bachelor’s degree and 12+ years of experience (or 14+ years of experience).
• Deep applied ML expertise across traditional ML and deep learning (gradient boosting, transformers, foundation model embeddings, etc.).
• Architect-level understanding of agentic AI systems, including tool use, retrieval, multi-step reasoning, and guardrails.
• Strong expertise in causal inference (uplift modeling, propensity scoring, etc.) and experimental design at scale.
• Proven experience operating ML in production at scale, including feature engineering, pipelines, and model monitoring.
• Proficiency in SQL and Python, with experience using ML/LLM tooling (Spark, Databricks, Snowflake) and frameworks (PyTorch, scikit-learn).
• Demonstrated ability to influence senior leadership and mentor high-level technical talent.

Preferred Qualifications

• Advanced degree in a quantitative field such as Statistics, Computer Science, Machine Learning, Economics, or Operations Research.
• Experience with lifecycle modeling (churn, expansion, adoption) and fluency in SaaS metrics like NRR, GRR, and ARR.

About the Company

Smartsheet empowers teams to manage work seamlessly and scale solutions smarter. We are currently uniting human teams with AI agents to automate manual tasks and uncover insights at scale, creating space for people to focus on judgment, creativity, and big thinking.