- Bachelor’s degree and 12+ years of experience (or 14+ years of experience); advanced degree in a quantitative field (Statistics, CS, ML, Economics, Operations Research, or similar) strongly preferred
- Track record of setting technical direction for applied ML and AI work that ships and matters — major initiatives, complex systems, or new modeling paradigms taken from idea to production impact
- Deep applied ML expertise across both traditional ML and deep learning: gradient boosting, regularized linear models, transformer-based sequence models, foundation model embeddings, causal ML, contextual bandits, and offline RL
- Architect-level grasp of agentic AI systems: tool use, retrieval, multi-step reasoning, evaluation, guardrails, and the patterns for keeping all of it reliable in production
- Strong grasp of causal inference for intervention design and lifecycle modeling: uplift modeling, difference-in-differences, propensity scoring, and synthetic control
- Solid foundation in statistics and experimental design at scale: hypothesis testing, power analysis, multiple comparisons, sequential testing, and quasi-experimental methods
- Experience operating ML in production at scale — feature engineering and pipelines, model monitoring, drift detection, retraining cadence, and the trade-offs between batch and real-time serving
- Proficient in SQL and Python; comfort with ML/LLM tooling at scale (Spark, Databricks, Snowflake, or equivalents), ML frameworks (PyTorch, scikit-learn, XGBoost/LightGBM), and visualization tools (Tableau or similar)
- Experience leading lifecycle modeling work — churn, expansion, adoption, plan health, lead/account scoring — and business fluency in the SaaS metrics that drive it (NRR, GRR, ARR, and cohort economics)
- A pragmatic production bar: latency, cost, monitoring, drift, hallucination, and what happens when the model or sub-agent is wrong
- Demonstrated ability to influence senior product and engineering leaders and to mentor staff and principal data scientists — your track record shows people and decisions, not just models, getting better
- Comfort operating in deep ambiguity – defining the problem, choosing the approach, and aligning the team when no playbook exists
Get to Know Us
At Smartsheet, your ideas are heard, your potential is supported, and your contributions have real impact. You’ll have the freedom to explore, push boundaries, and grow beyond your role. We welcome diverse perspectives and nontraditional paths—because we know that impact comes from individuals who care deeply and challenge thoughtfully. When you’re doing work that stretches you, excites you, and connects you to something bigger, that’s magic at work. Let’s build what’s next, together.