Stage septembre 2026 - Data Science et Machine Learning/AI practitionner (H/F/N) (50% client, 50% R&D)

Here's the job offer description formatted in Markdown, following your specifications: 📊 **About Ekimetrics** Companies that perform make better decisions. Since 2006, Ekimetrics has been helping organizations transform their decisions into a sustainable competitive advantage through AI solutions. Our dual ambition is to combine performance and sustainability to build lasting leadership. Our solutions are a unique combination of People and technology. Our Eki.Decisions platform complements the expertise of our marketing, sales effectiveness, and data science teams to connect AI to the decisions that structure the entire organization. With a 100% in-house team and offices in Paris, London, New York, Hong Kong, and Shanghai, we are committed to responsible and frugal AI to ensure a constant competitive advantage and remain true to our values and DNA. 📊 **Let's look at some data:** * 400 data science experts * 1000 diverse projects for over 350 clients * 5 offices: Paris, Hong Kong, Shanghai, London, and New York * $1 billion in profits generated for our clients since 2006 🌱 At Ekimetrics, we aim to help our clients rethink their business models by reconciling economic performance with sustainable objectives, thanks to data science. To achieve this, we have all the necessary in-house skills to meet our clients' needs: Product Managers, Product Designers, Data Architects, Lead Tech, Data Engineers, DevOps Engineers, Data Scientists. 🤝 **The Data Science Team You Could Join** **Why are we recruiting?** To support our strong growth, we are looking for a Data Science Intern. Our unique market positioning will allow you to combine a variety of statistical and learning skills – from econometric models to deep learning, including numerical optimization – with strategy to best address our clients' business challenges. **More specifically, your responsibilities will include:** * **Analysis of business needs**: Translate business needs into technical problems and define measurable objectives. * **Identification of technical solutions**: Collaborate with the team (seniors/managers) to identify approaches that meet the specific project requirements. * **Data processing & analysis**: Collaborate with data engineers to collect, clean, and preprocess the data needed to create models. Conduct exploratory analyses supported by relevant visualizations. * **Solution development**: Develop and implement identified machine learning models, optimize existing models, and develop new approaches to improve performance & ensure adherence to industrial code best practices. * **Communication and collaboration**: Present technical results clearly and accessibly to the team and clients & collaborate with other teams and clients to ensure effective integration of proposed solutions. * **Technological watch**: Stay up-to-date on technological advancements and trends in the data science and machine learning sector. **The profi