AI Savvy Data Analyst

Company Description

As of January 2026, Averna and Spherea joined forces to form the Spherea Group.  A global Test & Quality Solution leader, Averna Powered by Spherea partners with product designers, developers and manufacturers to help them achieve higher product quality, accelerate time to market and protect their brands by covering and offering solutions and expertise for the entire product lifecycle.  

Averna Powered by Spherea offers specialized expertise and innovative test, vision inspection, precision assembly and automated solutions that deliver substantial technical, financial and market benefits for clients in the aerospace, automotive, consumer electronics, defense, energy, industrials, medical devices & life sciences, semiconductor, telecom and transportation industries.   

Their solutions include prototyping & consulting, precision assembly & production, automated test solutions, in-line test systems, test system replication, and test platforms & products. Averna Powered by Spherea’s expertise ranges from vision systems, specialized battery test, RF & microwave and fiber optics to robotics & motion, instrumentation, control systems, and data management. 

Job Description

Data Analyst – AI focused in Hardware Manufacturing, Quality & Reliability

Role Summary

This role sits at the intersection of data analytics, hardware manufacturing, quality & reliability engineering, and digital transformation. As an AI‑savvy Data Analyst, you will generate value‑driven insights from fleet‑scale manufacturing, test, and deployment data while supporting New Product Introduction (NPI) and Product Operations teams.

You will transform complex manufacturing and quality concepts into data‑driven metrics, intelligent dashboards, and AI‑enabled applications. You will also lead initiatives that modernize manual workflows into scalable, automated, and insight‑driven systems—leveraging statistical analysis, cloud data platforms, and AI technologies.

Key Responsibilities

Data Analysis & Engineering

• Extract, transform, and analyze fleet‑scale manufacturing, testing, deployment, and operational data using advanced SQL (DML).
• Understand and translate manufacturing, quality, and reliability concepts into measurable, data‑driven solutions and KPIs.
• Perform statistical analysis on manufacturing test data to ensure data integrity, reliability, and readiness for automation and root‑cause analysis.
• Continuously provide feedback upstream to improve data quality, coverage, and performance.

AI, Automation & Intelligence

• Identify and implement opportunities to automate manual workflows using AI and advanced analytics.
• Develop AI‑driven recommendation systems for data standards, anomaly detection, intelligent data mapping, and quality insights.
• Support the integration of AI and ML services (e.g., Vertex AI, LLMs) into analytics workflows and intelligent applications.
• Partner with engineers and product teams to embed AI capabilities into hardware NPI and manufacturing processes.

Visualization, Reporting & Executive Insights

• Design, develop, and maintain interactive dashboards and reports using Looker Studio, Tableau, Power BI, or equivalent tools.
• Visualize manufacturing performance, data quality scores, operational metrics, headcount status, and organizational spending.
• Prepare executive‑level summaries and presentations that distill complex technical data into clear, actionable insights.
• Provide leadership with real‑time, decision‑ready visibility into manufacturing and operational health.

Cross‑Functional Collaboration & Program Support

• Interact professionally with engineers, product owners, suppliers, and subject‑matter experts across manufacturing, quality, IT, and operations.
• Provide technical guidance to suppliers and engineering teams on optimal data collection, standards, and data warehousing solutions.
• Support multiple parallel initiatives by tracking progress, identifying risks, and escalating delivery impediments when needed.
• Facilitate change management through documentation, communication plans, and process training.

Qualifications

The ideal candidate in a few words:

Required Qualifications

• Bachelor’s degree in Computer Science, Data Science, Data Analytics, Statistics, Mathematics, Engineering, or a related discipline.
• Advanced proficiency in SQL with strong understanding of data modeling and normalization best practices.
• Proficiency in Python (or R) for data analysis, including experience with t