Operations Research, Engineering Analytics

Job Details:
Job Description:

Intel's Foundry Technology Manufacturing (FTM) team seeks an Operations Research, Engineering Analytics professional to solve critical engineering problems through advanced software expertise, mathematical modeling, and research methodologies. You will develop strategic software applications, algorithms, and AI solutions to drive manufacturing excellence and ensure continued technological advancement in semiconductor operations.

Key Responsibilities

Engineering Problem Solving & Innovation

• Solve complex engineering problems critical for technology and product development using software expertise and domain knowledge
• Research technological trends and collaborate with industry, academic, and standardization groups to address technology and customer challenges
• Find innovative solutions to difficult problems for midterm and long-term timeframes
• Research to define boundaries, create proof of concepts, and prototype new ideas

Manufacturing Systems Engineering

• Design and develop system-wide software solutions applying engineering, mathematical, simulation, and optimization models
• Identify and solve complex problems in factory performance, loading, equipment performance, decision science, and distribution networks
• Build, develop, validate, and apply mathematically based decision algorithms, heuristics, optimization, and simulation models
• Develop software applications of complex engineering models for manufacturing environments

Strategic Solution Development

• Work closely with business units to identify root causes and define strategic and tactical needs
• Drive appropriate business and technical software solutions using formal technical training and engineering judgment
• Develop solutions utilizing business knowledge, analytical expertise, and manufacturing domain understanding
• Lead and manage projects while influencing varying levels of customer management and decision bodies

Advanced Analytics & Modeling

• Apply discrete-event predictive modeling and digital twin manufacturing simulations
• Implement advanced analytics and machine learning techniques including regression, clustering, neural networks, and classification
• Conduct data analysis, visualization, statistical analysis, and time series analysis
• Develop optimization solutions using linear and mixed-integer programming

Core Competencies

• Excellent team, interpersonal, analysis, and presentation skills
• Ability to lead and manage complex projects
• Strong influence and communication skills across management levels
• Engineering judgment and business acumen

Qualifications:

The Minimum qualifications are required to be initially considered for this position. Minimum qualifications listed below would be obtained through a combination of industry relevant job experience, internship experience and / or schoolwork/classes/research. The preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Minimum Qualifications

• Master of Science degree in Industrial Engineering, Operations Research, Computer Science or related quantitative field of study
• 2+ years of experience in discrete-event predictive modeling and digital twin manufacturing simulations
• 2+ years of experience in Oracle PL/SQL, Python, R, and applied statistics

Preferred Qualifications

• Advanced Analytics experience
• Analytics and machine learning experience with regression, clustering, neural networks, and classification
• Advanced experience in data analysis, data visualization, statistical analysis, and time series analysis
• Production planning and manufacturing automation experience
  Optimization experience with CPLEX and linear/mixed-integer programming

Job Type:

College Grad

Shift:

Shift 1 (United States of America)

Primary Location:

US, Arizona, Phoenix

Additional Locations:
Business group:

Intel Foundry strives to make every facet of semiconductor manufacturing state-of-the-art while delighting our customers - from delivering cutting-edge silicon process and packaging technology leadership for the AI era, enabling our customers to design leadership products, global manufacturing scale and supply chain, through the continuous yield improvements to advanced packaging all the way to final test and assembly. We ensure our foundry customers' products receive our utmost focus in terms of service, technology enablement and capacity commitments. Employees in the Foundry Technology Manufacturing are part of a worldwide factory network that designs, develops, manufactures, and assembly/test packages the compute devices to improve the lives of every person on Earth.

Posting Statement:

All qualified applicants will receive consideration for employment without regard to race, color, religion, religious creed, sex, national origin, ancestry, age, physical or mental disability, medical condition, genetic information, military and veteran status, marital status, pregnancy, gender, gender expression, gender identity, sexual orientation, or any other characteristic protected by local law, regulation, or ordinance.

Position of Trust

N/A

Benefits:

We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as, benefit programs which include health, retirement, and vacation. Find more information about all of our Amazing Benefits here:

Annual Salary Range for jobs which could be performed in the US: $109, ,860.00 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 Role

This 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.

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