Sr Principal Data Scientist
For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day.
Smartsheet is looking for a Sr. Principal Data Scientist to set the technical direction for the ML models and AI sub-agents that drive growth, monetization, efficiency, and retention across the customer lifecycle. You’ll architect the systems, define the modeling and evaluation standards, and shape the roadmap for how Smartsheet uses applied ML and agentic AI to serve millions of customers. The data is unusually rich: petabyte-scale execution data spanning two decades of how real work gets done. You are a recognized technical leader who moves fluidly between architecture, prototype, and production; raises the bar for the data scientists around you; and partners with senior product and engineering leaders to make decisions that compound across the org. You will work primarily with Product and Engineering and will be a part of Smartsheet’s Business Intelligence team.
This full-time position reports to the Director of Data Science and is based in Smartsheet’s Bengaluru, India office.
You Will:
Set the technical direction for how Smartsheet uses applied ML and agentic AI across the customer lifecycle — what gets built, what doesn’t, and what good looks like
Architect the systems behind the sub-agents: how they ground themselves in evidence, how risk and confidence are calibrated, how decisions are evaluated, and how all of it stays safe and trustworthy at scale
Define the modeling, evaluation, and experimentation standards the team follows — from offline metrics to online rollout to production monitoring
Personally ship the highest-leverage models and sub-agents — the ones that need a senior IC to frame the problem, push through ambiguity, and de-risk the approach
Drive technical decisions on the data foundations and knowledge layer sub-agents reason over, with strong stewardship of privacy, aggregation, and customer trust
Partner with senior Product, Engineering, and Applied AI leaders to shape strategy, roadmap, and investment
Raise the bar for the data science team — mentor staff and principal data scientists, review designs, set hiring standards, and grow the org’s modeling rigor
You Have:
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.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
#LI-Remote
Smartsheet is looking for a Sr. Principal Data Scientist to set the technical direction for the ML models and AI sub-agents that drive growth, monetization, efficiency, and retention across the customer lifecycle. You’ll architect the systems, define the modeling and evaluation standards, and shape the roadmap for how Smartsheet uses applied ML and agentic AI to serve millions of customers. The data is unusually rich: petabyte-scale execution data spanning two decades of how real work gets done. You are a recognized technical leader who moves fluidly between architecture, prototype, and production; raises the bar for the data scientists around you; and partners with senior product and engineering leaders to make decisions that compound across the org. You will work primarily with Product and Engineering and will be a part of Smartsheet’s Business Intelligence team.
This full-time position reports to the Director of Data Science and is based in Smartsheet’s Bengaluru, India office.
You Will:
Set the technical direction for how Smartsheet uses applied ML and agentic AI across the customer lifecycle — what gets built, what doesn’t, and what good looks like
Architect the systems behind the sub-agents: how they ground themselves in evidence, how risk and confidence are calibrated, how decisions are evaluated, and how all of it stays safe and trustworthy at scale
Define the modeling, evaluation, and experimentation standards the team follows — from offline metrics to online rollout to production monitoring
Personally ship the highest-leverage models and sub-agents — the ones that need a senior IC to frame the problem, push through ambiguity, and de-risk the approach
Drive technical decisions on the data foundations and knowledge layer sub-agents reason over, with strong stewardship of privacy, aggregation, and customer trust
Partner with senior Product, Engineering, and Applied AI leaders to shape strategy, roadmap, and investment
Raise the bar for the data science team — mentor staff and principal data scientists, review designs, set hiring standards, and grow the org’s modeling rigor
You Have:
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.
Equal Opportunity Employer:
Smartsheet is an Equal Opportunity (EEO) employer committed to fostering an inclusive environment with the best employees. It is our policy to provide equal employment opportunities to all qualified applicants in accordance with applicable laws in the US, UK, Australia, Germany, Costa Rica, Japan, Bulgaria, and India. All qualified applicants will receive consideration without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age, protected veteran or disabled status, or genetic information.
If there are preparations we can make to help ensure you have a comfortable and positive interview experience, please let us know.
#LI-Remote