Fleet Operations Specialist

Role: Fleet Operations BI Engineer

Location: Foster City, CA (Hybrid)

Duration: Long Term

Key Responsibilities:

• Data Processing & Cleanliness: Use SQL and Python to extract, clean, and process large datasets.
• Transform raw data into meaningful business metrics.
• Data Analysis & Reporting: Analyze fleet performance and operational data, identify trends, and provide insights to improve fleet capacity and operational efficiency. Create and maintain interactive
• dashboards that track key performance indicators (KPIs) and operational metrics.
• Visualization & Insights: Develop clear, concise visualizations and dashboards in Looker, Databricks, or equivalent tools to support operational decision-making. Ensure that these tools provide actionable insights for fleet operations and partner teams.
• Collaboration with Fleet Operations Teams: Work closely with Fleet Operations teams to understand barriers to performance and identify areas for improvement using rigorous analytical methods.
• Ad-Hoc Analysis: Complete ad-hoc analyses to help answer key business questions or evaluate the impact of potential changes to fleet operations. Identify trends in ad-hoc requests and propose business improvements.

Qualifications:

• Education: Bachelor’s or Master’s degree in data science, Business Analytics, Statistics, Computer Science, Engineering, or a related field.
• 3-5 years of experience in data analysis
• Strong proficiency in SQL and data warehousing for data extraction, transformation, and modeling.
• Proficiency with Python/R or equivalent for data cleaning, manipulation, and analysis.
• Experience working with Data engineering, Product, Tech, and Business teams to map data availability, set up pipelines, and create visibility into operational data.
• Experience creating and maintaining dashboards with tools like Looker, Tableau, Power BI, or similar visualization tools.

Skills & Competencies:

• Strong analytical mindset with a passion for problem-solving and driving operational improvements.
• Excellent communication skills, with the ability to explain technical concepts to a diverse, non-technical audience.
• Ability to translate complex data into clear, actionable insights for a non-technical audience.
• Ability to translate data requirements into clear deliverables across multiple interdependent teams.

Bonus Qualifications:

• Familiarity with machine learning or predictive analytics techniques to anticipate operational needs.
• Experience with workforce management, labor planning, or cost optimization analysis.
• Attention to detail and a commitment to ensuring data accuracy.