Senior Applied Data Scientist (Fleet Intelligence)

Location: Remote, available only in the United States, Canada, or Mexico

Company

hirify.global provides a software platform that helps organizations manage fleet operations, including maintenance, usage, costs, availability, and asset lifecycle decisions.

What you will do

• Deliver Fleet Intelligence initiatives covering tire intelligence, utilization intelligence, ROI measurement, predictive models, and analytical foundations.
• Develop projections and predictive models for fleet usage, maintenance cost, availability, condition, failure risk, and asset lifecycle decisions.
• Translate product questions into hypotheses, target variables, baselines, evaluation plans, and delivery milestones.
• Explore maintenance, usage, cost, work-order, telematics, warranty, and asset-history data to identify signals and data gaps.
• Build, validate, deploy, monitor, and iterate production-quality models.
• Partner with Product, Design, Software Engineering, and Data Engineering to make model outputs explainable and actionable.

Requirements

• 5+ years of experience in applied data science, machine learning, statistical modeling, or a related role.
• Track record of shipping models or decision-support systems that influenced customer or business outcomes.
• Strong proficiency in Python and SQL, including exploratory analysis, feature engineering, model development, and evaluation on large datasets.
• Strong knowledge of statistics and machine learning fundamentals, including validation, calibration, uncertainty, bias, and error analysis.
• Experience taking models from experimentation into production, including versioning, testing, deployment, observability, monitoring, and retraining.
• Experience with cloud data platforms and transformation workflows such as Snowflake, dbt, and orchestration tools, plus cross-functional communication skills.

Nice to have

• Experience in 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.
• Graduate study in a quantitative field or experience contributing to customer-facing software products.

Culture & Benefits

• Remote-working friendly since 2012.
• Health and dental coverage, vision insurance, FSA and HSA options, and disability coverage.
• 401(k) match of 4% and incentive stock options.
• Four weeks of PTO, company and floating holidays, and paid parental leave.
• Professional development, wellbeing, community service, and business expense funds.
• Mac laptop and new-hire equipment stipend.