Senior Applied Data Scientist, Fleet Intelligence
Core
Turn fleet maintenance and operational data into trusted intelligence for usage, cost, availability, maintenance risk, and asset lifecycle decisions.
Role type
Senior Applied Data Scientist (Fleet Intelligence)
Builds
Customer-facing fleet intelligence workflows and predictive models (via careerplan.io/jobs/5236170007-senior-applied-data-scientist-fleet-intelligence-at-fleetio)
Domain
Transportation / Fleet Management
Deliverable
production ML models
Required skills
Python, SQL, time-series forecasting, regression, classification, anomaly detection, survival analysis, model deployment, observability, feature engineering, statistics, uncertainty quantification
Preferred skills
fleet/transportation domain knowledge, maintenance cost modeling, semantic layers (ThoughtSpot/Cube), experimental design
Technologies
Snowflake, dbt, orchestration tools
Responsibilities
Develop predictive models for fleet usage, maintenance cost, and failure risk; translate product questions into hypotheses and evaluation plans; build and operationalize models from experimentation to production monitoring; define model-quality metrics and drift detection; partner with Product/Design to make outputs actionable; establish reusable practices for model validation and documentation.
Seniority
Senior, hands-on IC
