Impress employers and recruiters.
Choose from hundreds of resume examples.

Target Resume Now

Tailor your resume to this ASIC Quality Data Analyst role.

Rezi rewrites your resume against Ericsson's job description. Free.

Resume score gauge reading 58 out of 100

Don't guess if your resume is good enough.

See how it scores against the ASIC Quality Data Analyst posting at Ericsson — free, in seconds.

About the Role

ASIC Quality Data Analyst role focuses on analyzing factory and field failures, identifying failure signatures, and supporting root-cause investigations. The role integrates production test, manufacturing, repair, and field-return data to expedite failure diagnosis and root-cause determination, ultimately improving product quality.

Responsibilities

Own the analytical work supporting factory and field failure investigations, including data correlation, analytical tools, automated workflows, and reporting.
Work with internal factories, field organizations, Product Engineering, Test Engineering, Quality, and other engineering teams to develop evidence and evaluate failure hypotheses.
Engage semiconductor fabs and external manufacturing partners as needed to trace failures across the supply chain and support corrective actions.
Analyze factory production, test, repair, and field-return data to identify failure trends, recurring signatures, quality escapes, and emerging product risks.
Collaborate with Product Engineering, Test Engineering, ASIC Design, Reliability, Quality, Manufacturing, Validation, and System Debug teams to investigate factory and field issues and validate technical findings.
Develop and maintain tools, scripts, and analytical models that correlate factory and field data, identify recurring failure signatures, and prioritize hypotheses for engineering investigation.
Build and maintain automated data pipelines linking factory test, manufacturing history, repair records, and field returns, with the traceability needed to follow failures back to production lots, devices, and processes.
Apply statistical analysis and AI/ML techniques to detect abnormal failure patterns, group related returns, automate data analysis, and identify quality risks earlier.
Use production yield, screening, defect, wafer fab, and assembly/test data to investigate factory and field failures, assess quality escapes, and evaluate the effectiveness of process or test changes.
Develop dashboards and reporting tools to track factory failure rates, field returns, DPPM trends, recurring failure modes, and investigation progress, including time to diagnosis and root-cause confirmation.
Document analytical findings, present supporting evidence, and work with engineering and factory teams to confirm root causes and measure the effectiveness of corrective actions and screening changes.
Reduce the time needed to diagnose and root-cause factory and field failures by automating data preparation, correlating evidence across sources, and making relevant failure history available to investigation teams.

Requirements

Ability to identify failure modes contributing to factory defects and field escapes.
Experience providing failure signatures and analytical evidence to Product Engineering and Test Engineering to support test development and validation, reduce outgoing DPPM, and evaluate screening effectiveness.
3–5 years of experience in data analytics, engineering analytics, data science, or a related role in a semiconductor environment.
Hands-on experience with Python, SQL, data modeling, visualization, or comparable analytical tools.
Practical experience using statistical methods and AI/ML techniques for data analysis or workflow automation.
Strong analytical and problem-solving skills, including experience working with complex or inconsistent data from multiple sources.
Ability to collaborate across engineering disciplines and communicate technical findings clearly.
Experience in semiconductor manufacturing, factory test, product engineering, quality, reliability, failure analysis, or related hardware environments.
Familiarity with manufacturing failure data, production test results, repair records, field returns, and device traceability; exposure to wafer fabrication or assembly processes is beneficial.
Experience developing and maintaining analytical tools, automated workflows, anomaly-detection models, or predictive quality methods.
Experience with LLMs, AI agents, retrieval-augmented generation (RAG), or related AI frameworks.
Demonstrated experience using data to support failure investigations, improve screening, or reduce recurring manufacturing or field issues.

Skills

AI
Analytical capabilities
Python
SQL
Data modeling
Data visualization
Statistical analysis
AI/ML techniques
LLMs
AI agents
Retrieval-augmented generation (RAG)
AI frameworks

Location

Austin, Texas

Work Type

Hybrid
On-site

Experience Level

3-5 years

Education Level

Bachelor’s degree in Engineering, Computer Science, Data Science, Data Analytics, or a related field.

Salary/Compensations

The salary range for this position is dependent on various factors including, but not limited to, location, and the candidate’s combination of job-related knowledge, qualifications, skills, education, training, and experience.
Opportunity for an annual bonus based on business and individual performance.

Benefits

Choice of three medical plan options
Dental plan option
Company credits towards medical and dental premiums
Ericsson US 401(k) Plan with automatic 3% company contribution and matching contributions
Company credits for basic life insurance and basic accidental death and dismemberment coverage
Company credits for short-term and long-term disability coverage
Option to participate in Ericsson’s Stock Purchase Plan
15 days of accrued vacation
Up to 3 personal days per year
11 annual holidays
8 hours of volunteer time
80 hours of sick time annually
Up to 16 weeks of paid maternity leave
6 weeks of parental or adoption leave at 100% of pay
Financial wellness programs
Educational assistance
Matching gifts
Recognition programs

About the Company

Ericsson Silicon is expanding its custom ASIC capabilities for 5G Advanced and 6G.
The Central Engineering ASIC Quality team supports product quality and reliability throughout the ASIC lifecycle.
Ericsson uses a merit-based hiring approach that values people with different experiences, perspectives and skillsets.
Ericsson believes this approach drives innovation, which is essential for future growth.

Equal Opportunity

Ericsson is proud to be an Equal Opportunity employer.
If you need assistance or to request an accommodation due to a disability, please contact Ericsson at hr.direct.americas@ericsson.com.