Job Description

If you are looking for a challenging and exciting career in the world of technology, then look no further. Skyworks is an innovator of high performance analog semiconductors whose solutions are powering the wireless networking revolution. At Skyworks, you will find a fast-paced environment with a strong focus on global collaboration, minimal layers of management and the freedom to make meaningful contributions in a setting that encourages creativity and out-of-the-box thinking. We are excited about the opportunity to work with you and glad you want to be part of a team of talented individuals who together can change the way the world communicates.

Requisition ID: 76448 

Description


We are seeking a highly motivated Data Analyst Engineer to support the characterization and design of SAW and BAW filters. This role will focus on collecting, analyzing, and interpreting complex measurement data to extract meaningful insights that guide product design decisions. The ideal candidate will leverage machine learning (ML), artificial intelligence (AI), and advanced data analytics tools to model filter behavior and improve design efficiency. This position requires close collaboration with the IT department to ensure robust data infrastructure and automation capabilities.

Responsibilities


PRIMARY RESPONSIBILITY: Designs, develops and programs methods, processes, and systems to consolidate and analyze unstructured, diverse “big data” sources to generate actionable insights and solutions for client services and product enhancement. Interacts with product and service teams to identify questions and issues for data analysis and experiments. Develops and codes software programs, algorithms and automated processes to cleanse, integrate and evaluate large datasets from multiple disparate sources. Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers. This is a product engineering role in which employees work with multiple types of business data.

  • Collect, organize, and validate characterization data from SAW and BAW filter measurements.

  • Develop and maintain data pipelines and dashboards for real-time and historical analysis.

  • Apply machine learning and AI techniques to model filter behavior and predict performance trends.

  • Collaborate with design engineers to translate data insights into actionable design improvements.

  • Work closely with the IT department to ensure secure, scalable, and automated data handling systems.

  • Create clear and compelling visualizations and reports to communicate findings to cross-functional teams.

  • Support the development of tools and scripts for data preprocessing, feature extraction, and model training.

  • Ensure data integrity and compliance with internal standards and best practices.

    • Required Experience and Skills

  • Bachelor’s or Master’s degree in Electrical Engineering, Data Science, Computer Science, or related field.
  • Strong understanding of RF filter technologies (SAW, BAW) and their characterization methods.

  • Proficiency in Python, MATLAB, or R for data analysis and modeling.

  • Experience with machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch).

  • Familiarity with data visualization tools (e.g., Power BI, Tableau, matplotlib).

  • Knowledge of database systems (SQL, NoSQL) and data pipeline tools.

  • Excellent communication skills and ability to work in cross-functional teams.

  • Experience working with IT teams on data infrastructure, automation, and security.

    • Desired Experience and Skills

  • Experience in semiconductor or RF component industry.

  • Knowledge of statistical modeling and signal processing.

  • Familiarity with cloud platforms (e.g., Azure, AWS) for data storage and computation.

  • Experience with version control systems (e.g., Git) and collaborative development workflows.

    • Apply for this Position

    Ready to join ? Click the button below to submit your application.

    Submit Application