We’re looking for an intern to join our team. If you thrive on complex problems, love diving into “brain-scratching” challenges, and want your work to genuinely impact people’s lives, this role is for you. You’ll report directly to our CTO and Data Scientist, working on projects that have the potential to shape the way people take care of their mental health with teale.

We kept the below short on purpose: we don’t need a ‘know-it-all,’ we need someone thrilled to learn things they haven’t encountered before.

About the Role: Empowering Mental Health with Joy

You’ll play a key role in enhancing Joy, our mental health coach. Joy is a reasoning graph-based model designed to provide personalized support to our users. Your work will directly contribute to making mental health care more accessible and effective.

Key Responsibilities Include (but are not limited to):

• Therapy Protocol Modeling: Translate new therapy protocols into robust, scalable implementations (from algorithm design and testing to deployment alongside our development team).

• Algorithm Refinement & Optimization: Continuously improve Joy’s existing algorithms and underlying technical architecture for enhanced performance and user outcomes.

• Cross-Functional Collaboration: Partner closely with our Care team to understand user needs, clinical insights, and define future project roadmaps.

• Usage Analysis & Innovation: Analyze current platform usage data to identify new potential use cases for Joy and optimize existing functionalities.

During the internship, you may also contribute to other data science projects not related to Joy (e.g., data modeling to understand user’s interaction with the app)

• Academic Foundation:

  • Currently pursuing or recently completed a Master’s degree in a quantitative field (e.g., Mathematics, Statistics, Computer Science, Data Science, or a closely related discipline).

• Machine Learning (ML) & AI Fundamentals:

  • Solid understanding of core ML concepts, including supervised and unsupervised learning algorithms, model training methodologies, and evaluation metrics.

  • Familiarity with foundational AI concepts, particularly around Large Language Models (LLMs) such as their capabilities, limitations, and the basics of Retrieval Augmented Generation (RAG).

• Programming Skills:

  • Proficiency in Python, including practical experience with major data science libraries (e.g., NumPy, Pandas, Scikit-learn, and ideally a deep learning framework like TensorFlow or PyTorch).

  • Ability to work with APIs for data integration and model deployment.

• Nice to Have:

  • Interest in the Collatz conjecture.

1st interview with François, Data Scientist

2nd Interview with Gilles, CTO and co-founder

Coffee-chat with Karim, Data Analyst