Sr. Data Scientist II (Remote Eligible)

Smartsheet
United States
Workplace: RemoteFull timeUSD 155,000 - 185,000 annuallyFunction: Data Science & Machine LearningExperience: 8+ yearsEducation: bachelorsSkills: ["Curiosity","Technical rigor","Cross-functional communication","Partnership building","Ability to research and learn"]

Build ML models and AI sub-agents that drive growth, monetization, efficiency, and retention across the customer lifecycle. You’ll design and ship systems that combine predictive modeling, retrieved context, and LLM reasoning, develop lifecycle churn and health scoring models, and create knowledge layers with privacy-aware practices. Partner with Product and Engineering to deploy production solutions at scale, define metrics and experiments, and build evaluation harnesses to prevent regressions.

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FursaFursa
Smartsheet
Smartsheet
1 month ago

Sr. Data Scientist II (Remote Eligible)

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Last checked: 13 hours agoStatus: Live

Job Summary

Build ML models and AI sub-agents that drive growth, monetization, efficiency, and retention across the customer lifecycle. You’ll design and ship systems that combine predictive modeling, retrieved context, and LLM reasoning, develop lifecycle churn and health scoring models, and create knowledge layers with privacy-aware practices. Partner with Product and Engineering to deploy production solutions at scale, define metrics and experiments, and build evaluation harnesses to prevent regressions.
Location: United States
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Design and ship AI sub-agents that recommend or take action across the customer lifecycle using predictive models, retrieved context, and LLM reasoning.
  • •Build predictive and prescriptive models for churn risk, growth, adoption trajectories, account health scoring, and related lifecycle problems.
  • •Develop data foundations and a knowledge layer the sub-agents reason over with responsible aggregation and privacy-aware design.
  • •Create retrieval, grounding, and tool strategies for each sub-agent, including when to act, defer, recommend, or escalate.
  • •Define rollout metrics and experimentation strategy, build evaluation harnesses, and help ensure production readiness by catching regressions.

Pay and Benefits

Salary: USD 155,000 - 185,000 annually
Perks:Health InsuranceVisionDental401kStipendPaid LeaveSick TimeParental LeaveLife InsuranceLong-term DisabilityPaid HolidaysRemote WorkVolunteer Day

Key Requirements

  • •Bachelor’s degree and 8+ years of experience (or 10+ years); advanced degree in a quantitative field preferred.
  • •Deep applied ML expertise across traditional ML and deep learning, including gradient boosting, regularized linear models, transformer sequence models, embeddings, causal ML, contextual bandits, and offline RL.
  • •Strong causal inference skills for intervention design and lifecycle modeling (uplift modeling, difference-in-differences, propensity scoring, synthetic control).
  • •Solid statistics and experimental design foundation (hypothesis testing, power analysis, multiple comparisons, sequential testing, quasi-experimental methods).
  • •Hands-on production experience with LLM/agent systems, including tool use, retrieval, multi-step reasoning, evaluation, and guardrails.
Experience:8+ years
Education:Bachelor's
Skills:CuriosityTechnical rigorCross-functional communicationPartnership buildingAbility to research and learn
Languages:English
Tech Stack:SQLPythonSparkDatabricksSnowflakePyTorchScikit-learnXGBoostLightGBMTableauLLMMachine learningDeep learning

Company Brief

Smartsheet
Provides a cloud-based work management platform that enables teams to plan, track, automate, and report on work. Smartsheet combines spreadsheets, collaboration, and workflow automation to help organizations manage projects and processes at scale.
Industry: Enterprise Software
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Bellevue, United States
Founded: 2005
WebsiteLinkedIn