Applied Data Scientist & Statistician – AI/ML for Semiconductors

Intel; Phoenix (AZ); Hybrid; USD 116,010 - 228,070; Full time

Benefits offered by this job

Stock bonuses

Health benefits

Retirement plan

Job summary

Intel is seeking a Statistician and Data Scientist for the TD AI office in Phoenix. The role partners with factory automation to support semiconductor process development and transfer to the virtual factory network.

Responsibilities include applying AI/ML, building data-driven apps, and training others while communicating insights clearly. Hybrid work model with emphasis on data analytics and process control.

Qualifications

• Master's or PhD in Statistics, Data Science or Industrial Engineering.
• 4+ years in statistics or data science.
• 2+ years in quality systems like process control/change control.
• 1+ year in PowerBI or similar dashboards.
• 1+ year in data analytics and ML (Python, R, JMP) and relational databases (SQL).

Responsibilities

• Use AI/ML/Analytics algorithms to extract insights from structured data.
• Develop statistical methodologies for process control and change management.
• Code statistical analyses and data cleaning in Python, R, SQL, or JSL.
• Collaborate with analytics teams to solve business problems.
• Translate data into actionable intelligence for business strategy.

Skills

AI/ML analytics

Statistical methodologies

Statistical analysis

Data structures

Communication skills

Train others

Analytical problem solving

Teamwork

Ambiguity tolerance

Self-motivation

Data cleaning

Education

Master's or PhD in Statistics/Data Science/Industrial Engineering

Tools

PowerBI

Python

SQL

R

JSL

SPARK

Kubernetes

Hadoop

JMP

Job description

Intel is seeking a Statistician and Data Scientist for the TD AI office in Phoenix. The role partners with factory automation to support semiconductor process development and transfer to the virtual factory network.

Responsibilities include applying AI/ML, building data-driven apps, and training others while communicating insights clearly. Hybrid work model with emphasis on data analytics and process control.