Supply-Chain AI & Data Analytics Intern

Motorola Solutions; Chicago (IL); On-site; USD 30,000 - 33,000; Full time

Job summary

Motorola Solutions in Chicago is seeking an AI & Data Analytics Intern to develop a predictive supply chain risk tool. You will integrate internal metrics with external market data and build ML models to flag bottlenecks for planners.

The role involves creating dashboards using Power BI or Tableau and communicating insights to stakeholders, with a focus on end-to-end data-driven solutions for supply resilience.

Qualifications

• Pursuing a Bachelor’s degree in a related field with an expected graduation by 2029.
• Proficiency in Python or R and data science libraries (Pandas, NumPy).
• Experience with Power BI or Tableau for dashboards is preferred.
• Strong analytical and problem-solving skills with ability to translate data into business insights.

Responsibilities

• Develop data integration pipelines for internal metrics and external market data.
• Design, train, and validate predictive models (risk scoring, time-series forecasting, anomaly detection).
• Create prototypes or dashboards for supply chain planners and stakeholders.
• Communicate model results and insights to cross-functional teams.

Skills

Analytical problem-solving

Independent initiative

Translate data into business insights

Understanding of logistics and lead/采购

Education

Bachelor’s degree pursuit in Supply Chain Management, Logistics, Business Analytics, Operations, or related field

Graduation date not later than Dec 2029

Tools

Power BI

Tableau

Python

R

Scikit-learn

TensorFlow

PyTorch

Pandas

NumPy

Job description

Motorola Solutions in Chicago is seeking an AI & Data Analytics Intern to develop a predictive supply chain risk tool. You will integrate internal metrics with external market data and build ML models to flag bottlenecks for planners.

The role involves creating dashboards using Power BI or Tableau and communicating insights to stakeholders, with a focus on end-to-end data-driven solutions for supply resilience.