Data Scientist/Statistician

Intel Corporation
Phoenix, United States of America
yesterday

Role details

Contract type
Internship / Graduate position
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior
Compensation
$ 228K

Job location

Phoenix, United States of America

Tech stack

Artificial Intelligence
Data analysis
Cloud Storage
Continuous Delivery
Continuous Integration
Data Cleansing
Data Mining
Data Structures
Relational Databases
Github
R
Hadoop
HBase
Python
Machine Learning
Power BI
Standard Sql
Software Engineering
SQL Databases
Unstructured Data
Data Processing
JMP (Statistical Software)
Spark
Kubernetes
Process Control Systems
Apache Nifi
REST

Job description

Intel Foundry Statistics and Data Science team's mission is to drive statistically sound methodologies into business practices and systems to help organization manage change control decisions, monitor capability of the process, ensure matching across tools and fabs, and drive best in class process control systems. Our team reports into the foundry quality and reliability team and is essential for driving transformation of Intel to be focused on not just process development, but a great partner for our foundry customers to help turn data into information. Our team is looking for an engineer with background in statistics and data science with strong technical skills in applied statistics, good communication skills, ability to also help support and develop modern AI/ML solutions.

As a Statistician and Data Scientist in the TD AI office, you will partner with Intel's factory automation organization and Foundry TD's functional areas to support semiconductor process development and transfer of these systems to worldwide virtual factory network.

The primary responsibilities for this role will include, but are not limited to:

  • Ensuring organization leverages appropriate data and analyses to make change control decisions
  • Drives organization to use process control systems to improve capability, matching, and stability of semiconductor process technologies
  • Use predictive modeling, statistics, Machine Learning, Data Mining, and other data analysis techniques to collect, explore, and extract insights from the structure and unstructured data.
  • Develop software, algorithms and applications to apply mathematics to data, perform large scale experimentation and build data driven apps to translate data into intelligence, solve a variety of business problems and enable business strategy.
  • Assist the business with casual inferences; observations with finding patterns and relationships in data.
  • Interfacing with process and integration functional area analytics teams to help solve problems, 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.

Requirements

A successful candidate will have proven experience demonstrating the following skills and behavioral traits

  • Experience in using AI/ML/Analytics algorithms and methodologies
  • Developing statistical methodologies
  • Ability to code statistical analysis, data cleaning, and data manipulation via common languages such as JSL, Python, and SQL
  • Understanding of data structures
  • Strong written and oral communication skills.
  • Ability to train others
  • Analytical problem solving and troubleshooting skills.
  • Teamwork skills and partnership skills.
  • High tolerance of ambiguity.
  • High level of self-motivation, You must possess the minimum qualifications 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., * Master's or PhD degree in Statistics, Data Science or Industrial Engineering.
  • 4+ years working in statistics or data science
  • 2+ years working on quality systems such as process control systems and change control systems
  • 1+ year working on PowerBI or similar dashboards
  • 1+ years in data analytics and machine learning (Python, R, JMP, etc.) and relational databases (SQL)., * 1+ years working on fault detection systems
  • 2+ years in a Technical leadership role.
  • 3+ months working knowledge with any of following technologies: JSL, Python, Spark, NiFi, Hadoop, HBase, S3 object storage, Kubernetes, REST APIs and services.
  • 3+ months working knowledge with CI/CD (Continuous Integration/Continuous Deployment) and proficiency with GitHub and GitHub Actions.
  • Prior interaction with factory automation systems

Requirements listed would be obtained through a combination of industry relevant job experience, internship experiences and or schoolwork/classes/research.

Benefits & conditions

We 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 (https://intel.wd1.myworkdayjobs.com/External/page/1025c144664a100150b4b1665c750003) .

Annual Salary Range for jobs which could be performed in the US: $116,010.00-228,070.00 USD

About the company

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.

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