Dark Kitchen Analytics & Operations Intern

DiDi; Ciudad de México; Presencial; MXN 89.000 - 134.000; Jornada completa

Descripción de la vacante

DiDi is seeking a data analytics intern in Mexico City to help track and optimize its dark kitchen operations. You will analyze marketplace data, build dashboards, and contribute to performance improvement initiatives.

This role offers exposure to cross-functional teams and real-world business impact within a fast-paced environment. Ideal applicants are enrolled in a business, economics, engineering, data science, or statistics degree with strong analytical skills and knowledge of Excel, SQL,

Formación

• Strong analytical and quantitative problem-solving skills.
• Experience with Excel/Sheets (advanced functions) or SQL.
• Familiarity with Python or other analytical languages.
• Able to translate data into actionable insights.

Responsabilidades

• Track, clean, and analyze operational and marketplace data to identify performance drivers.
• Build dashboards and recurring reports to monitor KPIs like sales and delivery efficiency.
• Identify trends and anomalies to drive improvement opportunities.
• Support development of frameworks to improve kitchen performance and satisfaction.
• Conduct root-cause analysis to understand issues in partner operations.
• Assist in planning and executing A/B tests and pilots.
• Translate insights into recommendations for senior stakeholders.
• Prepare presentations and documentation for leadership reviews.

Educación

Enrolled in Business, Economics, Engineering, Data Science, Statistics

Herramientas

Excel/Sheets

SQL

Python

Data platforms

Descripción del empleo

DiDi is seeking a data analytics intern in Mexico City to help track and optimize its dark kitchen operations. You will analyze marketplace data, build dashboards, and contribute to performance improvement initiatives.

This role offers exposure to cross-functional teams and real-world business impact within a fast-paced environment. Ideal applicants are enrolled in a business, economics, engineering, data science, or statistics degree with strong analytical skills and knowledge of Excel, SQL,