Senior Applied Data Scientist, Fleet Intelligence

Responsibilities

• Help deliver near-term Fleet Intelligence initiatives, including tire intelligence, utilization intelligence, ROI measurement, existing predictive models, and the analytical foundations that support customer-facing intelligence.
• Evaluate and develop credible projections or predictive models for fleet usage, maintenance cost, availability, condition and failure risk, and asset lifecycle decisions as product direction and evidence mature.
• Translate product questions into clear hypotheses, target variables, baselines, evaluation plans, and incremental delivery milestones.
• Explore Fleetio’s maintenance, usage, cost, work-order, telematics, warranty, and asset-history data to identify predictive signals and material data gaps.
• Build, validate, and operationalize models from experimentation through production monitoring and iteration.
• Define model-quality metrics, confidence thresholds, drift detection, and feedback loops appropriate to the cost and reversibility of the customer decision.
• Partner with Product and
• Design to make model outputs understandable, explainable, and actionable inside the workflows where customers already make decisions.
• Establish reusable practices for experimentation, model documentation, validation, monitoring, and responsible claims about predictive performance.
• Communicate findings, tradeoffs, risks, and recommendations clearly to technical partners, product leaders, and executives.

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