Senior Applied Data Scientist, Fleet Intelligence

Fleetio
United States, Canada, Mexico
Workplace: RemoteFull timeFunction: Data Science & Machine LearningExperience: 5+ yearsSkills: ["Communication","Collaboration","Correctness","Explainability","Pragmatism"]

Build and operationalize Fleet Intelligence models that turn fleet maintenance and operational data into trusted, actionable predictions for customers. Assess current model quality and establish baselines, then develop near-term capabilities such as tire/utilization intelligence, ROI measurement, and predictive maintenance risk. Translate product questions into measurable modeling work, communicate uncertainty clearly, and help integrate model outputs into customer-facing workflows.

Loading

Loading job details...

Preparing the role view and application actions.

FursaFursa
Fleetio
Fleetio
11 hours ago

Senior Applied Data Scientist, Fleet Intelligence

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 1 hour agoStatus: Live

Job Summary

Build and operationalize Fleet Intelligence models that turn fleet maintenance and operational data into trusted, actionable predictions for customers. Assess current model quality and establish baselines, then develop near-term capabilities such as tire/utilization intelligence, ROI measurement, and predictive maintenance risk. Translate product questions into measurable modeling work, communicate uncertainty clearly, and help integrate model outputs into customer-facing workflows.
Location: United States, Canada, Mexico
Workplace: Remote
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Deliver near-term Fleet Intelligence initiatives including tire intelligence, utilization intelligence, ROI measurement, and predictive models with analytical foundations.
  • •Evaluate and develop credible projections or predictive models for fleet usage, maintenance cost, availability, condition and failure risk, and asset lifecycle decisions.
  • •Translate product questions into hypotheses, target variables, baselines, evaluation plans, and incremental delivery milestones.
  • •Explore fleet data sources (maintenance, usage, cost, work-order, telematics, warranty, asset history) to identify predictive signals and material data gaps.
  • •Build, validate, and operationalize models end-to-end, defining quality metrics, confidence thresholds, drift detection, and feedback loops while partnering with Product and Design to integrate outputs.

Pay and Benefits

Perks:Health InsuranceDentalVision401k MatchEquityRemote WorkParental Leave

Key Requirements

  • •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 real customer or business outcomes.
  • •Strong proficiency with Python and SQL for exploratory analysis, feature engineering, model development, and evaluation on large datasets.
  • •Strong grounding in statistics and machine learning fundamentals, including model selection, validation, calibration, uncertainty, bias, and error analysis.
  • •Experience moving models into reliable production workflows with versioning, testing, deployment, observability, monitoring, and retraining strategies.
Experience:5+ yearsMachine learningApplied data scienceDecision-support
Skills:CommunicationCollaborationCorrectnessExplainabilityPragmatism
Languages:English
Tech Stack:PythonSQLSnowflakeDbtThoughtSpotCube

Company Brief

Fleetio
Provides cloud-based fleet management software to help businesses track, manage, and optimize vehicle fleets through maintenance scheduling, fuel and mileage tracking, inspections, and integrations with telematics and accounting systems.
Industry: Logistics
Company Size: Large (251 to 1,000 employees)
Growth: Established Company
Headquarters: Birmingham, United States
Founded: 2012
WebsiteLinkedIn