- Company Name
- AXA en France
- Job Title
- Data Scientist - AXA Life and Health international (F/H) stage
- Job Description
-
**Job title:**
Data Scientist Intern – Life & Health International (F/H)
**Role Summary:**
A 6‑month, full‑time internship (starting February 2026) in a multinational environment focused on designing, developing, and industrialising data‑science solutions for health‑care. The intern will manage the complete data‑science project life cycle—business understanding, data engineering, model development, MLOps, and GenAI experimentation—to deliver high‑impact business use‑cases.
**Expectations:**
* Complete the internship with demonstrable deliverables.
* Work independently while collaborating with cross‑functional teams (product, data, IT).
* Apply rigorous experimental practices, ensure reproducibility, and maintain clear documentation.
* Communicate findings to both technical and non‑technical audiences.
* Deliver results within agreed timelines, respecting performance SLAs.
**Key Responsibilities:**
1. **Business Framing** – Translate business requirements into data‑science use‑cases; define objectives, KPIs, constraints, and acceptance criteria.
2. **Data Engineering** – Collect, ingest, clean, normalise, and quality‑check multi‑format health data; handle missing values and inconsistencies; build reproducible data pipelines.
3. **Modeling & ML** – Prototype, train, and evaluate supervised ML / NLP / OCR models; set benchmarks, optimise metrics (accuracy, recall, F1, AUC, calibration), and ensure experimental reproducibility.
4. **MLOps & Industrialisation** – Document models (model cards, limits, usage recommendations); integrate PoCs into existing workflows; monitor model health and maintain metadata.
5. **GenAI & Innovation** – Investigate generative‑AI applications (LLMs, Retrieval‑Augmented Generation); prototype solutions (e.g., automated translations, fraud detection).
6. **Communication** – Produce dashboards (Streamlit, Dash) and concise reports; present outcomes to stakeholders.
**Required Skills:**
* **Programming:** Python, pandas, NumPy, scikit‑learn; familiarity with Git, repo organisation, basic testing, and documentation.
* **ML & NLP:** Model evaluation (precision, recall, F1, AUC/ROC, PR, cross‑validation), feature engineering, data quality assurance.
* **OCR & Text Processing:** Text pre‑processing, tokenisation, embeddings, basic OCR pipelines.
* **MLOps:** Model deployment practices, monitoring, reproducibility.
* **Data Engineering:** Data ingestion pipelines, handling diverse formats, data cleaning, normalisation.
* **Visualization:** Building simple dashboards (Streamlit or Dash).
* **Soft skills:** Clear communication, analytical mindset, detail‑orientation, curiosity, autonomy, collaborative.
* **Language:** English – full fluency required.
**Required Education & Certifications:**
* Master’s (M2) or equivalent in Data Science, Computer Science, Applied Mathematics, AI/Machine Learning, or a related engineering/technology discipline.
* No mandatory certifications, but knowledge of industry tools and standards is preferred.