Stage Data Scientist

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: www.mirakl.com.

• Get to Know the Data Science Team That Powers the Mirakl Platform

• Analyze and prepare data: Learn best practices to explore and transform data to ensure quality and relevance for algorithms
• Prototype algorithms: Test and refine your ideas with your manager’s support
• Collaborate on productionization: Work with Data Engineers to make your solutions ready for real-world deployment
• Build dashboards: Showcase the relevance of your work and monitor production performance
• Present your results: Share your progress weekly with the team for feedback and guidance
• Explore advanced methods: Grow in a high-level technical environment with experts who can train you
• Join brainstorming and tech watch, and collaborate with other teams

• Developing a seller scoring model based on quality criteria
• Detecting anomalies in seller behavior
• Improving product recommendation models for catalog expansion

• Fine-tuning and optimizing inference performance of multimodal and text embedding models for a product retrieval system powering sponsored listings

• For the Catalog Transformer team: Training LLMs and VLMs to automate onboarding of sellers’ catalogs
• For the Media team: Automatically generating new media types from images for marketplace product pages: 3D, video

• You’re in the final year of a Master’s (Bac+5) at an engineering school or university in Computer Science
• You know Python and its data science ecosystem (pandas, sklearn, seaborn, dash)
• You’re familiar with data preparation techniques and feature engineering
• You understand statistics, machine learning, and deep learning algorithms
• You’re particularly interested in industrialization and scaling of data science models beyond experimental work
• You want exposure to cloud environments (Google Cloud, AWS, MS Azure)
• You enjoy teamwork
• You’re responsive, service-oriented, a good listener, and a strong communicator
• You’re curious, autonomous, and proactive

• Internship stipend Master 2: €1,600 per month
• A workplace that supports well-being and balance: breakfasts, fitness and yoga classes, after-work events, game nights
• Supportive mentoring from technical experts
• Regular feedback to help you grow and gain autonomy
• Immersion in a collaborative, passionate team eager to share knowledge and experience
• A unique opportunity to discover a fast-growing French unicorn and work with international teams
• Access to our Works Council discounts (tickets, etc.)
• Healthy body, healthy mind: with the Gymlib pass, take time for yourself
• Modern offices in the heart of Paris (right by the Eiffel Tower)
• Swile meal vouchers
• Transportation covered (50% Navigo, bike, etc.)

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.