Hiring: Senior Applied Data Scientist, Fleet Intelligence Company: Fleetio Location: United States Job Posted Time: 2026-09-12 12:47:39 Employment Type: Contract / Remote Target Skills & Keywords : Machine Learning, Python, Rails, SQL, Snowflake, dbt About the job 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. •Demonstrated capacity to identify data-quality limitations, recommend improvements, and collaborate with data engineers on pipelines and source reliability. Required Skills: •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. Qualifications: •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. Compensation: •Flexible work environment (work from home / hybrid options) •Multiple health/dental coverage options (100% coverage for employee, 50% for family) Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!