End-of-studies Internship - Data & AI Consultant M/F - Regions

The mission:

Through the internship, you will have the opportunity to put your skills into practice, learn from experts, and contribute to concrete and impactful projects.

Being a consultant means participating in projects that address both technical challenges and business-oriented issues concerning various sectors of activity (luxury, retail, banking/insurance, industry, etc.).

Our missions combine a technical and operational dimension allowing you to deepen your knowledge on innovative topics. You will be involved in the entire data lifecycle to develop and maintain our clients' strategic data applications. During your projects, you will be led to work on the following elements:

• You will participate in framing client needs and in the reflection on the methodologies and architectures to implement to provide answers through Data and AI,

• You will identify, integrate, and structure data (sources, ETL/ELT connectors, modeling) to transform raw data into actionable and reliable Key Performance Indicators (KPIs),

• You will perform in-depth analyses and design models (statistical, machine learning, AI algorithms, agent-based) to address complex issues (customer behavior, predictive, optimization),

• You will showcase your results and industrialize your solutions, by creating reporting tools for business teams and applying best programming practices,

• You will demonstrate a strong appetite for the AI ecosystem, by staying updated on innovations, experimenting with new uses, and developing AI modules/solutions whenever the subject lends itself to it.

Depending on your appetite and desires, a subject with a technical or business focus will be assigned to you.

Below are examples of subjects:

• Optimization of order preparation in-store with a constrained optimization algorithm,

• Use of Gen AI to extract information from PDF documents and generate synonyms to improve document search,
• Implementation of a churn score by department and by store using Interpretable Machine Learning methods,
• Implementation of a segmentation of visits based on e-commerce website navigation data,
• Identify stores with seasonal characteristics in terms of revenue, in order to adjust weekly budgets and optimize the targeting of marketing campaigns,
• Development of a dashboard dedicated to the Management Control department of a large ready-to-wear group to analyze monthly the customer profile who contributed to revenue,
• Development of conversational agents (LLMs) to query sales data and implementation of AI use cases.

Lab’ AVISIA:

In addition to our missions, we conduct various internal projects that fuel our research and development. These projects give us the opportunity to offer our clients innovative analytical approaches, tested in real-world conditions.

To support these initiatives, we have established our own infrastructures. Our consultants thus benefit from the latest resources and market solutions for their learning, including "early adopter" versions to test before their general release.

Our commitments:

After implementing a solid internal CSR policy, we decided to dedicate our skills to sustainable development-oriented projects. A dedicated initiative was born: AVISIA Impact.

This initiative is thus our response to contribute directly (through our projects) and indirectly (through team training) to sustainable transformation challenges. We want to facilitate the emergence of future change agents and accelerate the pace of change.

For more information on these data initiatives for sustainable transformation, please visit our dedicated page Data For Impact.

The Human Factor:

We are therefore looking for talents who:

• Have excellent interpersonal skills,

• Are willing to be involved in the success of client projects,

• Possess strong analytical and synthesis skills,

• Place particular importance on the quality of deliverables and presentation,

• Are curious and keen to stay informed about market developments,

• Have the desire to continue learning to be active participants in their progression.

Skills:

You are in your final year of data studies at university or a top-tier school and possess the following skills:

• Very good knowledge of SQL and Python,

• Good knowledge of main machine learning algorithms,

• Ability to explain complex concepts in a simple and pedagogical way,

• Good knowledge of generative AI tools (Gemini, ChatGPT…) and assisted development tools (GitHub Copilot, Cursor, Claude Code...) to optimize daily efficiency,

• Bonus: You have some knowledge of cloud technologies (e.g., Google Cloud Platform, AWS, Azure, Snowflake...) and/or a market software solution for data processing and analysis (e.g., Dataiku, Databricks…)