Product Lifecycle & Data Analytics Analyst

Applied Materials, Inc.; Santa Clara (CA); On-site; USD 80,000 - 110,000; Full time

Benefits offered by this job

Stock award program

Competitive benefits

Relocation assistance

Bonus eligibility

Job summary

Applied Materials, Inc. is seeking a data analytics-focused professional to join our semiconductor solutions team in Santa Clara, CA. You will apply data analytics to service agreements, parts replacement, and spares to identify trends and guide strategy development.

You will work with Python, SQL, Tableau, and ERP/PLM tools, translating complex data into actionable insights, collaborating with engineers, product managers, and field stakeholders to drive growth and operational excellence.

Qualifications

• Bachelor's degree in Analytics, Engineering, Product Marketing, Product Management, or related field.
• Experience in Semiconductor or adjacent industries is highly desirable.
• Strong data analytics, stakeholder communication, and problem-solving skills.
• Experience with web applications development and data tools (Python/SQL/Tableau).

Responsibilities

• Apply data analytics to service agreements, parts replacement, and spares to identify trends and guide strategy development.
• Interpret engineering data and provide strategic recommendations based on statistical analysis.
• Track competitor activity and centralize intelligence for business decisions.
• Collaborate with cross-functional teams to define market opportunities and growth plans.

Skills

Data analytics

Python

SQL

Tableau

AI/ML knowledge

Stakeholder communication

Problem solving

Education

Bachelor's degree in Analytics, Engineering, Product Marketing, Product Management, or related

Tools

React/Angular/Vue

SAP

Job description

Applied Materials, Inc. is seeking a data analytics-focused professional to join our semiconductor solutions team in Santa Clara, CA. You will apply data analytics to service agreements, parts replacement, and spares to identify trends and guide strategy development.

You will work with Python, SQL, Tableau, and ERP/PLM tools, translating complex data into actionable insights, collaborating with engineers, product managers, and field stakeholders to drive growth and operational excellence.