Senior Applied Data Scientist, Fleet Intelligence

🕒 September 11

🌐 United States, Canada, +1 more countries – Remote

🇺🇸 United States – Remote 🇨🇦 Canada – Remote 🇲🇽 Mexico – Remote

⏰ Full Time

🟠 Senior

📊 Data Scientist

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 12%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Fleetio

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2012

📦 Logistics

💼 Consulting

🚗 Transport

💰 $21.1M Series B on 2020-11

Logistics • Consulting • Transport

Fleetio is a comprehensive fleet management software provider that helps organizations track, analyze, and improve their fleet operations. The platform offers tools for vehicle maintenance, tracking fuel usage, managing drivers, and ensuring regulatory compliance. Fleetio aims to enhance efficiency and reduce costs for businesses with fleets of all sizes by providing real-time data and insights.

📋 Description

• Deliver near-term Fleet Intelligence initiatives, including tire intelligence, utilization intelligence, ROI measurement, existing predictive models, and analytical foundations for customer-facing intelligence • Evaluate and develop 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 maintenance, usage, cost, work-order, telematics, warranty, and asset-history data to identify predictive signals and 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 • Partner with Product and Design to make model outputs understandable, explainable, and actionable in customer workflows • Establish reusable practices for experimentation, model documentation, validation, monitoring, and responsible predictive-performance claims • Communicate findings, tradeoffs, risks, and recommendations to technical partners, product leaders, and executives • Share knowledge through design reviews, documentation, pairing, and mentorship

🎯 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, including 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 with time-series forecasting, regression, classification, ranking, anomaly detection, survival or reliability analysis, or optimization; depth in several areas more important than breadth across all • Experience taking models beyond notebooks into reliable production workflows, including versioning, testing, deployment, observability, performance monitoring, and retraining or refresh strategies • Experience using modern cloud data platforms and transformation workflows such as Snowflake, dbt, and orchestration tools • Ability to identify data-quality limitations, recommend improvements, and collaborate with data engineers on pipelines and source reliability • Excellent written and verbal communication, particularly when explaining complex methods, uncertainty, and tradeoffs to non-specialists • Experience working cross-functionally with Product, Design, Software Engineering, and Data Engineering

🏖️ Benefits

• Multiple health/dental coverage options (100% coverage for employee, 50% for family) • Vision insurance • Incentive stock options • 401(k) match of 4% • PTO - 4 weeks (increases at year two!) • 12 company holidays + 2 floating holidays • Parental leave - birthing parent (16 weeks paid) non-birthing (4 weeks paid) • FSA & HSA options • Short and long term disability (short term 100% paid) • Community service funds • Professional development funds • Wellbeing fund - $150 quarterly • Business expense stipend - $125 quarterly • Mac laptop + new hire equipment stipend • Fully stocked kitchen with tons of drinks & snacks (BHM only) • Remote working friendly since 2012