Data Scientist Graduate Intern To Develop ML Pipeline

Job Details:

Job Description:

Intel is shaping the future of technology to help create a better future for the entire world. Our work in pushing forward fields like AI, analytics, and cloud-to-edge technology is at the heart of countless innovations. With a career at Intel, you'll have the opportunity to use technology to power major breakthroughs-such as self-driving cars and rebuilding coral reefs-and create enhancements that improve our everyday quality of life.

Join us and help make the future more wonderful for everyone.

In this role the Data Scientist Graduate Intern will develop ML pipelines for multiple independent data domains across multiple products by extending existing singular domain pipeline. The project is part of silicon photonics. The individual is expected to develop models to predict downstream performance based on upstream data. To be effective in this role you will be required to work a minimum of 20 hours per week.

Length of internship estimate is 3 months with a possibility to extend.

Qualifications:

You must possess the below 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. Experience listed below would be obtained through a combination of your schoolwork/classes/research and/or relevant previous job and/or internship experiences. This is an entry level position and will be compensated accordingly.

Minimum Qualifications:

• Must be pursuing Masters or PhD in Computer Science, Data Science, or related field.
• Experience with machine learning in an academic or commercial setting.
• Experience with Python, R and SQL.

Preferred Qualifications:

• Experience with Hadoop Ecosystem and/or Spark data processing.
• Software engineering skills such as unit test, CICD, DEV Ops and version control systems highly desired.

Job Type:

Student / Intern

Shift:

Shift 1 (United States of America)

Primary Location:

US, New Mexico, Albuquerque

Additional Locations:

US, California, San Jose, Virtual US

Intel strongly encourages employees to be vaccinated against COVID-19. Intel aligns to federal, state, and local laws and as a contractor to the U.S. Government is subject to government mandates that may be issued. Intel policies for COVID-19 including guidance about testing and vaccination are subject to change over time.

Business group:

The Network & Edge Group brings together our network connectivity and edge into a business unit chartered to drive technology end to end product leadership. It's leadership Ethernet, Switch, IPU, Photonics, Network and Edge portfolio is comprised of leadership products critically important to our customers.

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: https://www.intel.com/content/www/us/en/jobs/benefits.html

Annual Salary Range for jobs which could be performed in

US, Colorado, New York, Washington, California:$63,000.00-$166,000.00

Salary range dependent on a number of factors including location and experience.

Work Model for this Role

This role is available as a fully home-based and generally would require you to attend Intel sites only occasionally based on business need. This role may also be available as 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.