Data Science & AI Analytics Intern

Panera Bread is hiring a Data Science & AI Analytics Intern in Newton, MA. When: Summer 2027. Posted November 11, 2026. Checked against the employer's posting on November 12, 2026.

Data Science & AI Analytics - Summer 2027 Internship Program Data Science & AI Analytics Intern Team: Data Engineering & Analytics About the role Our Data Engineering & Analytics team builds the data, reporting and AI that help Panera run its cafés and serve its guests.

As an intern, you will work on real projects with real business impact, not side assignments. You will work alongside our data engineers, BI developers and analytics partners, and you will present what you built to leadership at the end of the internship.

What you’ll work on • Demand forecasting: Help measure how accurate our sales and transaction forecasts are, compare models against a baseline, and explain the results in plain English.

• Conversational analytics and AI agents: Explore how conversational analytics and AI agents on Looker can help business users get answers from our data faster.

• Predictive and prescriptive analytics: Help build and test predictive and prescriptive analytics that go beyond reporting what happened to recommending what to do next.

• Data quality and governance: Profile key datasets, flag gaps or anomalies, and help document KPI definitions so everyone uses the same numbers. • Insights and storytelling: Turn analysis into clear visuals and recommendations for business stakeholders.

What we are looking for Must have • Pursuing a degree in Data Science, Analytics, Computer Science, Statistics, MIS or a related field • Working knowledge of SQL and Python • Coursework or projects in statistics or machine learning • Curiosity, ownership, and the ability to explain technical work simply Nice to have • Exposure to a cloud data platform (BigQuery, etc.

) • Experience with Looker or Power BI • Familiarity with time-series forecasting • Interest in restaurants, retail or consumer businesses The actual pay offered will be determined by multiple factors, including but not limited to the candidate’s relevant experience, job-related knowledge, skills, and geographical location.

Individual compensation decisions are dependent upon the facts and circumstances of each position and candidate.