Senior Applied Data Scientist, Fleet Intelligence
Senior Applied Data Scientist on Fleetio's Fleet Intelligence team, turning fleet maintenance and usage data into customer-facing predictive models (tire and utilization intelligence, ROI, maintenance risk). Day-to-day is applied modeling in Python and SQL on large datasets, using Snowflake and dbt, and shipping models into production product workflows. Fully remote across USA, Canada, and Mexico.
- Compensation
- Not disclosed
- Location
- Remote - USA, CAN, MEX
- Work setup
- Remote
- Seniority
- Senior
- Employment
- Contract
- Experience
- 5+ years
- Category
- Data science
- Posted
Skills
Must have
- 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 (exploratory analysis, feature engineering, model development, evaluation on large datasets)
- Strong grounding in statistics and ML fundamentals: model selection, validation, calibration, uncertainty, bias, error analysis
- Experience with time-series forecasting, regression, classification, ranking, anomaly detection, survival/reliability analysis, or optimization
- Experience taking models beyond notebooks into production workflows (versioning, testing, deployment, observability, monitoring, retraining)
- Experience with 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
- Excellent written and verbal communication, especially explaining complex methods and uncertainty to non-specialists
- Experience working cross-functionally with Product, Design, Software Engineering, and Data Engineering
Nice to have
- 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
Full 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:
- Our careers page:
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:
- Engineering culture, interview process, and videos:
- Fleetio overview video:
- More about the Fleetio platform:
- API docs:
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.