Job Details:Job Description:The Advanced Packaging Technology and Manufacturing (APTM) Yield Systems Organization is seeking a curious, thoughtful, and highly motivated Data Scientist with strong analytical capabilities and excellent communication skills. In this role, you will collaborate with yield analysts, engineers, and business partners to identify manufacturing yield challenges and translate them into scalable, data-driven system solutions that improve operational efficiency and product quality.
The ideal candidate combines expertise in data science, automation, AI/ML, computer vision, and software development with a passion for solving complex manufacturing problems. You will play a key role in developing dynamic solutions that enhance yield performance, reduce manual effort, and strengthen APTM's overall technical capabilities.
Key Responsibilities- Partner with yield analysts, engineers, and business stakeholders to understand manufacturing yield issues and convert business needs into clear system requirements.
- Design, develop, and deploy scalable data science solutions that address yield-related challenges across advanced packaging manufacturing operations.
- Create automated workflows and data pipelines that improve efficiency, accuracy, and decision-making.
- Apply machine learning, artificial intelligence, statistical analysis, and computer vision techniques to identify patterns, detect anomalies, and drive yield improvements.
- Develop and maintain software tools, dashboards, and applications that provide actionable insights to manufacturing teams.
- Leverage manufacturing and fabrication (fab) data to generate dynamic, real-time solutions that enhance operational performance.
- Collaborate across multidisciplinary teams to implement and support production-ready systems.
- Communicate technical findings, recommendations, and project outcomes effectively to both technical and non-technical audiences.
- Continuously evaluate emerging technologies and methodologies to improve APTM's yield analysis and manufacturing capabilities.
Behavioral traits:- Excellent communication and collaboration skills to influence cross-functional stakeholders, and tolerance to ambiguity for quickly changing environments.
- Proactive and self-driven with minimal supervision.
Qualifications:Minimum qualifications are required to be initially considered for this position. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.
This position is not eligible for Intel immigration sponsorshipMinimum Qualifications- Bachelor's degree with 3+ years of relevant experience or master's degree with 2+ years of relevant experience in Computer Science, Data Science or any other Engineering discipline.
- Experience mentioned above should be in the following areas:
- Experience working with advanced packaging data as well as Fab data (defects, yield, FDC, etc.) for more than 1 year
- Python programming for frontend and backend system pipeline development including data parsing, ETL pipelines, UI development framework for data visualization, database integration with both relational (e.g. MySQL, PostgreSQL) and NoSQL instances (e.g. MongoDB), and API development.
- Git for version control and CI/CD pipelines for automated deployment.
- 1 year or more experience with defect data workflows and automation systems (Fab Tools, Station Controllers and Adaptive Metrology).
Preferred Qualifications- 1 year or more of Layer owner experience, DefMet tool exposure or Fab experience (tool ownership, yield/integration, etc.)
- 1 year or more experience with UDB, YAS data structures and workflows.
- Experience building and troubleshooting ETL flows using Intel databases, especially with unstructured or missing advanced packaging/manufacturing data
- Experience supporting production data flows, dashboards, or tools used by engineering teams
- Experience working with cross-functional teams including process, yield, integration, metrology, automation, or data teams
- Experience managing multiple projects simultaneously against varying priorities within the team
- Hands-on experience with end-to-end data engineering workflow from data ingestion, cleaning, analytics, modeling, evaluation, and deployment.
- Execution of data science POCs into scalable and deployable solutions
- Working knowledge of GAJT and SQL Pathfinder, analytics packages like R, JMP
- Working knowledge of Git workflows, CI/CD pipelines, containerization, and Kubernetes for infrastructure and deployment management.
- Experience with segmenting and troubleshooting day to day issues utilizing any relevant logs to identify and providing recommendations/implement fixes
- Working experience building queries around the different Intel databases with a clear understanding of the location of data across these databases
- Experience utilizing Klarity/ICE
- A general understanding of fab and APTM process flow and tool functionality
Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research
Job Type:Experienced Hire
Shift:Shift 1 (United States of America)
Primary Location:US, New Mexico, Albuquerque
Additional Locations:US, Arizona, Phoenix, US, Oregon, Hillsboro
BenefitsWe offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock bonuses, and benefit programs which include health, retirement, and vacation. Find out more about the benefits of working at Intel.
Annual Salary Range for jobs which could be performed in the US: $136,900.00-193,270.00 USD
The range displayed on this job posting reflects the minimum and maximum target compensation for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific compensation range for your preferred location during the hiring process.
Work Model for this RoleThis role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. * Job posting details (such as work model, location or time type) are subject to change.
ADDITIONAL INFORMATION: Intel is committed to Responsible Business Alliance (RBA) compliance and ethical hiring practices. We do not charge any fees during our hiring process. Candidates should never be required to pay recruitment fees, medical examination fees, or any other charges as a condition of employment. If you are asked to pay any fees during our hiring process, please report this immediately to your recruiter.
