Overview
Remote
Depends on Experience
Accepts corp to corp applications
Contract - Independent
Contract - W2
Contract - 7 Month(s)
Skills
Artificial Intelligence
Machine Learning (ML)
Fleet Management
Data Analysis
Data Science
cloud platform experience
Job Details
Job Title: Data Analyst AI & Predictive Modeling for Fleet Operations
Location: Remote Job Type: 6 month+
Position Summary:
- We are seeking a detail-oriented and forward-thinking Data Analyst to join our Fleet Data Analytics team. This role will focus on developing an AI-driven predictive model aimed at improving data-driven decision-making, optimizing fleet operations, and supporting strategic initiatives.
- As fleet data grows in complexity and volume, this position is critical in helping the organization derive timely, accurate, and actionable insights. You will work with large, multi-source datasets and apply advanced analytics techniques to enhance operational efficiency and planning capabilities across the fleet.
Key Responsibilities:
- Design, build, and maintain predictive analytics models using AI and machine learning techniques to support fleet management and strategic decision-making.
- Apply advanced analytics and machine learning techniques to forecast fleet performance, identify operational risks, and support optimization efforts.
- Analyze large datasets from multiple platforms, ensuring data integrity, consistency, and completeness.
- Collaborate with stakeholders across departments to understand business needs and implement data-driven solutions that enhance fleet performance and efficiency.
- Identify patterns, anomalies, and opportunities within fleet data (e.g., utilization, maintenance, fuel consumption, downtime).
- Develop dashboards, reports, and visualizations to communicate insights to technical and non-technical stakeholders.
- Continuously monitor and refine models based on real-world performance, feedback, and evolving business goals.
- Stay current on trends and best practices in AI, data science, and predictive analytics applicable to fleet operations.
Qualifications:
- Bachelor s or Master s degree in Data Science, Statistics, Computer Science, Engineering, or a related field.
- 3+ years of experience in data analysis, machine learning, or AI model development.
- Proficiency in Python, R, SQL, or equivalent tools for data modeling and analysis.
- Experience with data visualization tools (e.g., Power BI, Tableau, or similar).
- Demonstrated ability to develop and deploy predictive models using regression, time-series forecasting, classification, or clustering.
- Experience working with large datasets and cloud-based data platforms (e.g., AWS, Azure, or Google Cloud Platform).
- Strong problem-solving and communication skills with the ability to translate analytical insights into strategic recommendations.
Preferred Skills:
- Knowledge of fleet operations, transportation logistics, or asset lifecycle management.
- Experience with real-time analytics or streaming data.
- Familiarity with MLOps, automated model deployment, or model monitoring.
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