AI & Data Analytics Intern - Supply Resilience

Company Overview At Motorola Solutions, we believe that everything starts with our people. We’re a global close-knit community, united by the relentless pursuit to help keep people safer everywhere. We build and connect technologies to help protect people, property and places. Our solutions foster the collaboration that’s critical for safer communities, safer schools, safer hospitals, safer businesses, and ultimately, safer nations. Connect with a career that matters, and help us build a safer future.

Department Overview Seeking an innovative, data-driven AI & Data Analytics Intern to lead the development of an intelligent, predictive supply chain risk assessment tool. In this role, you will leverage internal enterprise data, external market intelligence, and advanced machine learning models to build an AI solution capable of forecasting supply chain disruptions before they impact operations.

Job Description Are you ready to build data-driven solutions that protect and strengthen global supply chains? As the AI & Data Analytics Intern - Supply Resilience, you will integrate internal metrics—such as lead times, supplier performance, and inventory levels—with external market data, including geopolitical risks, weather events, commodity prices, and trade tariffs. In this hands-on role, you will design and validate predictive machine learning models (such as risk scoring, time-series forecasting, and anomaly detection) to flag supply bottlenecks and vendor risks before they occur. Using tools like Python/R and Power BI or Tableau, you will transform model outputs into actionable dashboards for supply chain planners and communicate key insights to business stakeholders.

This Internship Includes Data Integration & Pipeline Development: Identify, aggregate, and ingest internal supply chain metrics (lead times, supplier performance, inventory levels) alongside external market data (geopolitical risks, weather events, commodity price trends, trade tariffs).

AI/ML Model Development: Design, train, and validate predictive algorithms (e.g., risk scoring, time-series forecasting, anomaly detection) to flag potential supply bottlenecks and vendor risks.

Tool & Interface Creation: Build a functional prototype/dashboard or integrate model outputs into an actionable tool for supply chain planners.

Market Research & Feature Engineering: Analyze macro-market trends to engineer features that improve model accuracy and early-warning alerts.

Documentation & Communication: Present model logic, accuracy benchmarks, and actionable insights to key stakeholders and operations teams.

Additional Qualified Skills

• Power BI, or Tableau for user interface creation.
• Python or R, Scikit-learn, TensorFlow or PyTorch, Pandas, NumPy
• Analytical problem-solving, independent initiative, ability to translate complex data into business insights
• Desired: Understanding of logistics, lead times, procurement dynamics, and risk factors

Basic Requirements

• Currently pursuing a Bachelor’s degree in Supply Chain Management, Logistics, Business Analytics, Operations, or a related field
• Graduation date not later then Dec.2029

Travel Requirements

None

Relocation Provided

None

Position Type

Intern

EEO Statement Motorola Solutions is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion or belief, sex, sexual orientation, gender identity, national origin, disability, veteran status or any other legally-protected characteristic.

We are proud of our people-first and community-focused culture, empowering every Motorolan to be their most authentic self and to do their best work to deliver on the promise of a safer world. If you’d like to join our team but feel that you don’t quite meet all of the preferred skills, we’d still love to hear why you think you’d be a great addition to our team.

We’re committed to providing an inclusive and accessible recruiting experience for candidates with disabilities, or other physical or mental health conditions. To request an accommodation, please complete this Reasonable Accommodations Form so we can assist you.