Fleetio
Senior Applied Data Scientist, Fleet Intelligence
Remote - USA, CAN, MEX +1 · Remote · Senior · Full-time · Posted Sep 11, 2026
- Location
- Remote - USA, CAN, MEX
Remote - Experience
- 5+ years of experience in applied data science, machine learning, statistical modeling, or a closely related role.
About the job
Develop and ship production-ready predictive models and decision-support intelligence that help fleet customers make better operational, maintenance, cost, and asset-lifecycle decisions.
What you'll do
- Build, validate, operationalize, and monitor projections and predictive models for Fleet Intelligence initiatives.
- Translate product questions into hypotheses, baselines, evaluation plans, and incremental delivery milestones.
- Partner with Product, Design, Engineering, and Data teams to make model outputs understandable and actionable in customer workflows.
What they ask for
- 5+ years of experience in applied data science, machine learning, statistical modeling, or a closely related role.
- Track record of developing and shipping models or decision-support systems that influenced customer or business outcomes.
- Strong proficiency with DBT, Python, and SQL, plus grounding in statistics and machine learning fundamentals.
- Experience taking models into reliable production workflows and working cross-functionally with product and engineering teams.
Nice to have
- Experience in fleet, transportation, maintenance, reliability, asset management, insurance, logistics, or another operational domain.
- Familiarity with semantic layers and analytics tools such as ThoughtSpot or Cube.
Tools
DBT, Python, SQL, Snowflake, dbt, ThoughtSpot, Cube
AI focus
Apply statistical modeling and machine learning to fleet usage, maintenance cost, availability, condition and failure risk, and asset lifecycle decisions; assess model quality, uncertainty, and predictive opportunities.
Model-written summary · the original posting is authoritative