Manufacturing Data Analyst

Responsibilities

• Translate operational challenges and data pain points into structured analytics requirements by defining clear metrics and delivering actionable, data-driven insights to support decision-making.
• Design and automate end-to-end data workflows—including extraction, transformation, storage, and visualization—across systems such as Jira, SAP, 3DX, MES, and Ignition.
• Build and maintain scalable, user-friendly dashboards (e.g., Looker, Tableau) that monitor critical KPIs, including first pass yield, inbound cycle time, non-conformance rates, and equipment utilization.
• Lead cross-functional analytics initiatives by scoping workstreams, aligning stakeholders, establishing realistic timelines, and driving projects to completion.
• Improve data quality and reliability by leading data hygiene efforts and standardizing KPI definitions across teams to ensure consistent, trustworthy reporting.
• Develop and maintain intermediate datasets, bridge fragmented data sources, and contribute to data model design to prepare the organization for scalable analytics and future AI/ML integration.

• Bachelor’s degree in Computer Science, Data Analytics, Statistics, or related discipline
• 5+ years of hands-on experience in operations analytics, business intelligence, or technical problem-solving within manufacturing, logistics, or service operations.
• Proficiency in SQL, Excel, and emerging AI tools, with a strong ability to analyze and interpret complex datasets.
• Demonstrated success in designing and maintaining dashboards and reports using tools such as Tableau, Looker, or Power BI.
• Proven ability to work cross-functionally with operations and technical teams to frame problems, define metrics, and deliver actionable insights.
• Strong communication and data storytelling skills, with the ability to present complex insights to non-technical stakeholders and drive alignment on decisions.

• Master’s degree in Business Analytics, Industrial Engineering, Data Science, or related discipline.
• Experience with manufacturing execution systems (MES), logistics systems (SAP, EWM ), or engineering systems (3DX).
• Working knowledge of lean manufacturing, test operations, logistics workflows, and key metrics like first-pass yield, PO cycle time, and NC tracking.
• Proficiency in advanced analytics tools (Python, R) and experience driving KPI standardization or data quality initiatives across teams.
• Familiarity with data modeling, dashboard governance, and preparing datasets for scalable analytics or future AI/ML integration.

If you need an accommodation to participate in the application or interview process please reach out to accommodations@zoox.com or your assigned recruiter.

You do not need to match every listed expectation to apply for this position. Here at Zoox, we know that diverse perspectives foster the innovation we need to be successful, and we are committed to building a team that encompasses a variety of backgrounds, experiences, and skills.