Senior Applied Data Scientist, Fleet Intelligence
New
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FleetioFleet Management
Remote - USA, CAN, MEXFull-TimeSenior
Salary not disclosed
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Job Details
- Experience
- 5+ years
- Required Skills
- PythonSQLMachine LearningSnowflakedbt
Requirements
- 5+ years of experience in applied data science, machine learning, or statistical modeling.
- Proven track record of developing and shipping models or decision-support systems.
- Strong proficiency with Python and SQL for analysis and model development.
- Strong grounding in statistics and machine learning fundamentals.
- Experience with time-series forecasting, regression, classification, or anomaly detection.
- Experience taking models to production, including versioning, testing, and observability.
- Experience with cloud data platforms and transformation workflows such as Snowflake and dbt.
- Ability to collaborate with data engineers on pipelines and source reliability.
- Excellent communication skills for explaining complex methods and tradeoffs.
- Experience working cross-functionally with Product, Design, and Engineering teams.
Responsibilities
- Deliver fleet intelligence initiatives like tire and utilization intelligence, ROI measurement, and predictive models.
- Translate product questions into clear hypotheses, baselines, and evaluation plans.
- Explore maintenance, usage, and telematics data to identify predictive signals and data gaps.
- Build, validate, and operationalize models through production monitoring.
- Define model quality metrics, confidence thresholds, and drift detection.
- Partner with Product and Design to integrate model outputs into customer workflows.
- Establish practices for model documentation, validation, and performance monitoring.
- Communicate findings and tradeoffs to technical and non-technical stakeholders.
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