About Analog Devices

Analog Devices, Inc. (NASDAQ: ADI ) is a global semiconductor leader that bridges the physical and digital worlds to enable breakthroughs at the Intelligent Edge. ADI combines analog, digital, AI, and software technologies into solutions that combat climate change, reliably connect humans and the world, and help drive advancements in automation and robotics, mobility, healthcare, energy and data centers. With revenue of more than $11 billion in FY25, ADI ensures today's innovators stay Ahead of What's Possible. Learn more at www.analog.com and on LinkedIn and X .

We are seeking a technically strong Data Analyst to work at the intersection of data analytics, device testing, and data systems within our Healthcare Biosensors group, focused developing a portfolio of novel biosensing products for a range of medical applications, including point-of-care diagnostics and therapeutics.
The role emphasises deep analytical capability applied to real-world device, test, and reliability data, supported by robust data pipelines, version-controlled workflows, and scalable data systems. This is a hands-on data analysis role focused on extracting insight from complex engineering datasets, building reproducible analytical workflows, and enabling data-driven decision-making across development and manufacturing.

Roles & Responsibilities

• Lead analysis of device, test, and reliability data to generate actionable insights.
• Develop repeatable analytical workflows using SQL and Python.
• Apply statistical methods (trend analysis, variance analysis, anomaly detection) to support decision-making.
• Analyse production and yield data to identify trends and root causes.
• Implement version-controlled analysis workflows (e.g. GitHub) to ensure reproducibility.
• Work with large datasets using appropriate data systems (e.g. cloud platforms, data lakes).
• Develop dashboards and visualisations to communicate analytical insights (Power BI or similar).
• Define metrics and KPIs with engineering teams.
• Document analysis methods and outputs for traceability and reuse.

Qualifications & Requirements

Required

• Degree in Engineering, Computer Science, Data Analytics, or a related discipline.
• 4–8 years’ experience in data analysis roles.
• Strong Python and SQL skills.
• Experience analysing test, validation, reliability, or manufacturing data.
• Proven ability to structure and analyse complex datasets.
• Experience using Git (e.g. GitHub) for version-controlled workflows.
• Ability to communicate data insights to technical stakeholders.
• Strong documentation and collaboration skills.

Desired

• Experience with large-scale data systems (e.g. cloud platforms, data lakes, distributed databases).
• Experience analysing high-volume datasets (e.g. test data, sensor data, reliability data).
• Exposure to regulated industries (e.g. medical devices, automotive).
• Experience integrating data from multiple sources.
• Experience applying statistical or ML techniques in an applied context.

Role Fit

Good fit if you:

• Are a data analyst first, focused on insight generation.
• Enjoy working with complex, real-world datasets.
• Use structured and reproducible approaches to analysis.
• Work effectively with engineering teams.

Not suited for:

• Pure ML or algorithm research roles.
• BI-only or reporting-only roles.

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For positions requiring access to technical data, Analog Devices, Inc. may have to obtain export licensing approval from the U.S. Department of Commerce - Bureau of Industry and Security and/or the U.S. Department of State - Directorate of Defense Trade Controls. As such, applicants for this position – except US Citizens, US Permanent Residents, and protected individuals as defined by 8 U.S.C. 1324b(a)(3) – may have to go through an export licensing review process.

Analog Devices is an equal opportunity employer. We foster a culture where everyone has an opportunity to succeed regardless of their race, color, religion, age, ancestry, national origin, social or ethnic origin, sex, sexual orientation, gender, gender identity, gender expression, marital status, pregnancy, parental status, disability, medical condition, genetic information, military or veteran status, union membership, and political affiliation, or any other legally protected group.