Data Scientist

Job Description

Manufacturing, Supply Chain and Operations Automation is seeking a Data Scientist to develop advanced analytic capabilities to support Intel's semiconductor manufacturing. The scope includes creating machine learning and analytic models and APIs to drive analytic discovery, and monitoring applications.

The candidate will create predictive models to track factory performance (cycle time, throughput, product outcomes and yields) by analyzing historical data from such sources as parametric, image and equipment or factory signals data. The candidate will be expected to apply analytic and software solutions in a fast-paced and complex business environment and be able to communicate complex technical analysis to both senior technical and also non-technical staff.

The ideal candidate should exhibit the following behavioral traits:

• Problem solving skills
• Analytical skills
• Skills to work in a dynamic, results, and team oriented environment
• Communication skills
• Skills to influence, strategic thinking, and leadership skills
• Skills to understand and streamline business strategies, stakeholder, and supplier management

Qualifications

You must possess the below minimum qualifications to be initially considered for this position. Preferred qualifications are in addition to the minimum qualifications and are considered a plus factor in identifying top candidates.

Candidate must possess the degree by employment start date. Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Minimum Qualifications:

• Master's degree in Electrical Engineering, Computer Science, Statistics, Mathematics, Physics, or equivalent quantitative field with a focus on Data Analytics and Machine learning.

Demonstrated understanding in 1 or more of the following skills:

• Analytic programming languages such as Python, R or SAS.
• Data mining and statistics as it relates to data analysis.
• Data munging, and reporting/visualization skills.

Preferred Qualifications:

Demonstrated understanding in any of the following skills:

• Relational databases (SQL) and no-SQL databases.
• High-Dimension data analysis, factorization techniques and MDS.
• Machine learning models including probability and statistical models in addition to time series analysis.
• Applying modern ML techniques such as support vector machines, categorical and regression trees, neural networks and recommendation systems.

Inside this Business Group

As the world's largest chip manufacturer, Intel strives to make every facet of semiconductor manufacturing state-of-the-art -- from semiconductor process development and manufacturing, through yield improvement to packaging, final test and optimization, and world class Supply Chain and facilities support. Employees in the Technology Development and Manufacturing Group are part of a worldwide network of design, development, manufacturing, and assembly/test facilities, all focused on utilizing the power of Moore’s Law to bring smart, connected devices to every person on Earth.

Other Locations

US, NM, Albuquerque; US, AZ, Phoenix

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.

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.

Working Model

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. In certain circumstances the work model may change to accommodate business needs.