Analytics Engineer Intern

About Mirakl

Mirakl is the leading provider of eCommerce software solutions. Mirakl's suite of solutions provides enterprises with a transformative way to drive significant growth and efficiency in their online business.

Since 2012, Mirakl has been pioneering the platform economy, empowering retail and b2b enterprises with the most advanced, secure and scalable technology to digitize and expand product assortment through marketplace and dropship, improve efficiency in supplier catalog management and payments, personalize shopping experiences, and boost profits through retail media.

Mirakl is trusted by Macy's, Saks, Henry Schein, The Knot, 1800-Flowers, Best Buy, Lowe's, Ulta and 450+ industry-leading businesses worldwide. For more information:

Our Analytics Engineer team manages customer data and insights at Mirakl, and serves as the primary point of contact for anyone needing to understand our customers, products, and the company as a whole.

As Analytics Engineer Intern, you will play a critical role in building and optimising data models, pipelines, and solutions to securely, efficiently, and autonomously provide Mirakl workers with high-quality data to accelerate decision-making (Analytics) and optimize workflows (AI agents).

Responsibilities:

• Work closely Product & business teams to understand needs and develop valuable data solutions
• Develop and maintain data models & semantic layer (documentation) to convert raw data into analytics-ready datasets
• Develop and support self-service analytics and agentic solutions, empowering users to independently discover insights and optimize workflows.
• Build and maintain dashboards guaranteeing reliable access to critical performance indicators
• Drive adoption of analytics solutions through user training, responsive support and incident resolution

Your profile:

• You are looking for a 6-month internship starting between January and March 2026.
• You are doing a Masters degree in Data Science, Statistics, Computer Science, or a related field.
• Fluent in French and English.
• Proficient in SQL and python.
• Experience with the manipulation and transformation of very large data sets.
• Solid understanding of data modeling concepts and techniques (e.g. star schemas, normalisation etc.).
• Experience with forecasting and statistical analysis techniques; knowledge of machine learning models is a plus.
• Excellent problem-solving skills and the ability to work independently as well as in a team.

What we offer:

• Internship compensation: between €1200 and €1600 per month (depending on profile).
• A workplace that promotes well-being and balance: breakfasts, sports and yoga classes, after-work drinks, game nights...
• A tailor-made onboarding process to quickly acquire skills.
• Empowering and evolving responsibilities to make the most of this experience.
• A unique opportunity to discover a fast-growing French unicorn and work with international teams.
• Access to our CSE discounts (ticketing, etc.)
• A healthy mind in a healthy body: take time for yourself with the Gymlib pass
• Modern offices in the heart of Paris (at the foot of the Eiffel Tower).
• Swile meal vouchers card.
• Coverage of transportation costs (50% Navigo pass, bike, etc.)

Recruitment process:

• An initial call with the recruiter.
• Two interviews where you will have the opportunity to meet your future manager and colleague. The STAR method and structured interviews will hold no secrets for you.

We welcome collaborators with their diverse perspectives and experiences to power us forward. These often far exceed conventional job requirements and help us create a culture of continuous learning. If you're ready to join a global leader powering digital transformation for 450+ of the world's most innovative retailers and B2B organizations, we strongly encourage you to apply to any of our roles, even if you think you're not an exact match.

We may use Artificial Intelligence (AI) solutions to help streamline our hiring process, including screening applications, analyzing resumes, and assessing responses. While AI helps us work efficiently, all final hiring decisions are made by humans. For more information, visit our AI Guidelines for Candidates and Interviews.