- Company Name
- Banque Populaire Grand Ouest
- Job Title
- Stage - Data Scientist (F/H)
- Job Description
-
**Job Title:**
Data Science Intern (F/H)
**Role Summary:**
Provide a 6‑month data‑science internship focused on increasing digital channel sales for a banking institution. Develop and deploy predictive models to identify customers likely to transact online, collaborating with business experts and participating in end‑to‑end model delivery and business experimentation.
**Expectations:**
- Execute the full data‑science pipeline: project scoping, data preparation, model selection, hyper‑parameter tuning, interpretability, and production deployment.
- Work closely with business teams to translate analytics insights into actionable commercial actions.
- Maintain rigorous documentation, reproducible workflows, and ensure models meet performance and compliance standards.
**Key Responsibilities:**
- **Project Scoping:** Liaise with domain experts to define objectives and deliverables.
- **Model Strategy:** Evaluate statistical and machine‑learning techniques appropriate to available data and business goals.
- **Data Preparation:** Extract, clean, transform, and engineer features from SQL databases to create model‑ready datasets.
- **Model Development:** Build, train, and optimize predictive models; tune hyper‑parameters to maximize accuracy and generalization.
- **Interpretability:** Conduct model‑explainability studies (e.g., SHAP, LIME) to provide clear, actionable insights.
- **MLOps Deployment:** Design and implement deployment pipelines (CI/CD, containerization, monitoring) for seamless integration into existing architecture.
- **Business Experimentation:** Collaborate on designing, launching, and measuring digital‑channel campaigns that test model performance in real‑world conditions.
**Required Skills:**
- Proficiency in Python (pandas, scikit‑learn, XGBoost, TensorFlow/PyTorch optional) and SQL.
- Solid understanding of statistical modeling, supervised learning, and model evaluation metrics.
- Experience with data cleaning, feature engineering, and model interpretability tools.
- Familiarity with MLOps practices: model versioning, containerization (Docker), CI/CD pipelines.
- Strong analytical mindset, attention to detail, and teamwork ability.
- Excellent written and verbal communication in English; French skills are a plus.
**Required Education & Certifications:**
- Current Master’s student or equivalent in Data Science, Statistics, Computer Science, or related field.
- Academic coursework covering statistical methods, machine learning, and database systems.
- No specific certifications required, but knowledge of data‑science certifications (e.g., Microsoft Certified: Azure Data Scientist Associate, Google Professional ML) is advantageous.