Senior Applied Data Scientist, Fleet Intelligence

Fleetio; United States; Remote; USD 150,000 - 190,000; Full time

Benefits offered by this job

Health/dental coverage (employee 100%,

Vision insurance

Incentive stock options

401(k) match

PTO 4 weeks

Parental leave

FSA & HSA options

Disability insurance

Professional development funds

Remote-friendly policies

Job summary

Fleetio is seeking a Senior Applied Data Scientist within the Fleet Intelligence team. You will transform years of fleet data into trusted, actionable intelligence to inform usage, cost, availability, maintenance risk, and asset lifecycle decisions.

You’ll work at the intersection of data science, ML, analytics engineering, and product development, collaborating with Product Managers, Designers, Software Engineers, and Data partners.

Qualifications

• 5+ years in applied data science, ML, or related role.
• Track record shipping models that influenced outcomes.
• Strong Python and SQL skills for analysis and evaluation.
• Experience with time-series forecasting, anomaly detection, or related methods.
• Experience deploying models into production and monitoring.

Responsibilities

• Deliver near-term Fleet Intelligence initiatives (e.g., tire/utilization intelligence, ROI measurement).
• Develop credible projections or predictive models for fleet usage, maintenance cost, availability, and asset lifecycle decisions.
• Translate product questions into hypotheses, baselines, evaluation plans, and milestones.
• Explore maintenance, usage, cost, work-order, telematics data to identify predictive signals.
• Build, validate, and operationalize models from experimentation through production monitoring.
• Define model-quality metrics, confidence thresholds, drift detection, and feedback loops.
• Partner with Product/Design to make model outputs understandable and actionable in workflows.
• Establish reusable practices for experimentation, documentation, validation, monitoring, and responsible claims.

Skills

Applied data science

Machine learning

Statistical modeling

Python

SQL

Time-series forecasting

Experiment design

Production ML

Data engineering collaboration

Tools

Snowflake

dbt

Orchestration tools

Cloud data platforms

Job description

A little about us Fleetio is a modern software platform that helps thousands of organizations worldwide manage their fleet operations. Transportation technology is a hot market, and we’re leading the charge with raving fans and new customers signing up every day. We raised $450M in our Series D funding round in March of 2025 and are on an exciting trajectory as a company. Fleetio is also a proud founding member of the Rails Foundation!

More about our team and company:

Fleetio overview video: https://www.youtube.com/watch?v=YoXyXTFWbkg

Our careers page: https://www.fleetio.com/careers

Fleetio is looking for a product-minded Senior Applied Data Scientist to join our Fleet Intelligence team. You will help turn years of fleet maintenance and operational data into trusted, actionable intelligence that helps customers anticipate what is ahead and make better decisions about usage, cost, availability, maintenance risk, and asset lifecycle.

This is an applied role at the intersection of data science, machine learning, analytics engineering, and product development. You will work closely with Product Managers, Designers, Software Engineers, and Data partners to identify valuable prediction problems, develop practical models, and bring them into customer-facing workflows. Your goal is to deliver intelligence that changes a decision, arrives early enough to act on, and communicates uncertainty honestly.

Your initial mandate will be grounded in confirmed Fleet Intelligence work: utilization and tire intelligence, ROI measurement, existing predictive models, and the analytics foundations needed to support customer-facing intelligence. You will assess current model quality, establish credible baselines, and help the team ship useful capabilities while strengthening its data-science practices.

Over time, you will help evaluate and shape opportunities for Predictive Fleet Intelligence, including projection, anticipation, and risk inference. You will help determine which opportunities are technically credible, valuable to customers, and ready to become durable product investments.

More About Our Team and Company

Watch our culture videos: https://fleet.io/culture

Engineering culture, interview process, and videos: https://www.fleetio.com/careers/engineering

Fleetio overview video: https://www.youtube.com/watch?v=IlvIbwZT3oU

More about the Fleetio platform: https://www.fleetio.com/features

API docs: https://developer.fleetio.com

This is a remote opportunity and is open to candidates in the United States, Canada, or Mexico.

Who You Are

You are an applied data scientist who enjoys working on ambiguous, high-value product problems. You can translate a customer or business decision into a measurable modeling problem, establish a credible baseline, and iteratively improve it. You know when straightforward statistics or deterministic projection is the right answer and when a machine learning approach is warranted.

You care deeply about correctness, explainability, and trust. You are comfortable communicating confidence intervals, limitations, and data gaps to technical and non-technical partners. You collaborate well with software and data engineers, but you can independently explore data, build production-quality models, define evaluation methods, and guide how model outputs should appear in a product experience.

You are pragmatic, product-minded, and outcome-oriented. You would rather ship a useful, well-calibrated forecast than an impressive model that does not change a customer decision.

Your Impact

• 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.
• Share knowledge through design reviews, documentation, pairing, and mentorship across Fleet Intelligence and adjacent teams.

Your Experience

• 5+ years of experience in applied data science, machine learning, statistical modeling, or a closely related role.
• A 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 of these areas is more important than breadth across all of them.
• 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 in support of applied modeling work.
• 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.

Considered a Plus

• Experience with fleet, transportation, maintenance, reliability, asset management, insurance, logistics, or another operational domain.
• Experience modeling maintenance cost, equipment failure, remaining useful life, warranty exposure, utilization, demand, or asset replacement decisions.
• Familiarity with semantic layers and analytics tools such as ThoughtSpot or Cube.
• Experience designing experiments or evaluating recommendations when randomized testing is impractical.
• Experience contributing to customer-facing software products or collaborating closely with full-stack product engineers.
• Graduate study in statistics, data science, computer science, operations research, applied mathematics, economics, or a related quantitative field.

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 #LI-Remote

Fleetio provides equal employment opportunities to all employees and applicants and prohibits discrimination and harassment. We celebrate diversity and are committed to creating an inclusive environment for all. All employment is decided on the basis of qualifications, merit and business need.

This application is not intended to and does not create a contract or offer of employment. Employment with Fleetio is at will.

If you have a disability or a special need that requires an accommodation to fill out the online application, please let us know by calling [phone].