Data Analytics Intern: AI Insights & Dashboards (Hybrid)

Pernod-Ricard; Paris; Hybride; EUR 16 000 - 17 000; Plein temps

Avantages offerts par ce poste

Company restaurant

Coursera training access

Masterclasses and events

Résumé du poste

Pernod Ricard invites a Data Analyst Intern to join the Artificial Intelligence team in Paris. You will work on data prep, analytics, and dashboarding to support marketing and commercial insights. The role focuses on automating data processes and delivering valuable analyses within a 6‑month window.

You will collaborate with Data Scientists, Data Analysts, and ML Engineers, gaining exposure to statistical methods and business intelligence tools in a fast-paced environment.

Qualifications

• Currently enrolled in a business school or master's in statistics, computer engineering, marketing or equivalent.
• Hands-on experience with at least one coding language (SQL, Python, etc.) and visualization tools (Power BI, Tableau, etc.).
• Fluent in English; French is a plus.

Responsabilités

• Participate in data preparation for statistical models and ensure data quality.
• Collaborate with Data and Tech teams during product deployment.
• Support data analysis to address strategic questions from affiliates or global functions.
• Create and maintain dashboards to communicate insights and monitor product performance.
• Automate data processes and enhance analytics workflows, proposing new tools or features.

Connaissances

SQL

Python

Power BI

Tableau

Statistics

Formation

Enrollment in business school or master's in statistics/CS/marketing

Outils

Power BI

Tableau

Excel

Description du poste

Pernod Ricard invites a Data Analyst Intern to join the Artificial Intelligence team in Paris. You will work on data prep, analytics, and dashboarding to support marketing and commercial insights. The role focuses on automating data processes and delivering valuable analyses within a 6‑month window.

You will collaborate with Data Scientists, Data Analysts, and ML Engineers, gaining exposure to statistical methods and business intelligence tools in a fast-paced environment.