Early Career Product Analyst, Supply Chain & Logistics

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Requirements:

• BA/BS or Master's degree in a quantitative field such as Statistics, Computer Science, Engineering, Mathematics, or Data Science.
• Experience in data engineering or a technical role with a heavy focus on SQL for data analysis, ETL design, and providing actionable insights, particularly in operational and supply chain contexts.
• Expertise in SQL-based data manipulation, with extensive experience in scripting, extracting large datasets, and designing complex ETL workflows.
• Demonstrated ability to closely collaborate with business, product, engineering, research, and design teams to influence and inform decision-making throughout the product lifecycle.
• Proficiency in creating and managing dashboards using Looker, Tableau, or similar BI tools.
• Deep passion for addressing real user problems through data-driven solutions.

Responsibilities:

• Perform in-depth analyses using a variety of analytical and statistical measurement techniques to drive key product and business decisions
• Partner with our Product and Engineering teams to automate operational processes
• Optimize driver planning by building operation models
• Provide insights on driver hiring strategy, performance, and retention
• Perform growth and expansion analyses through demand forecasting and inventory planning
• Identify opportunities and quantify impact of product launches through experimentation and measurement
• Architect and build production data models that elevate data-driven decisioning
• Provide clean, transformed data ready for analysis
• Maintain data documentation and definitions
• Define and apply best practices for data modeling and DWH architecture design
• Act as a critical thought partner and collaborate closely with Product, Research, Engineering, Growth, and Operations
• Recommend solutions that drive meaningful impact for our patients and partners
• Measure impact of the initiatives launched using various analytical and statistical techniques to drive further improvements
• Influence product strategy and drive roadmaps through insights and recommendations
• Contribute to defining our team and company data culture through peer collaboration, coaching, and input into the team processes we adopt as we grow the Analytics team together