- Company Name
- BNP Paribas Fortis
- Job Title
- Data Scientist
- Job Description
-
**Job Title**
Data Scientist
**Role Summary**
Design, develop, and deploy AI solutions that solve business challenges across virtual assistance, employee productivity tools, and internal process automation. Apply advanced language models, speech, image, and classical machine‑learning techniques while ensuring scientific rigor, responsible AI practices, and production readiness.
**Expectations**
- Minimum 3 years of experience building AI applications (generative and traditional).
- Strong foundation in core AI technologies; continuous learning of emerging methods.
- Deliver results with rigorous evaluation, error analysis, and robust deployment pipelines.
- Communicate findings effectively to stakeholders and managers.
**Key Responsibilities**
1. Develop AI models and applications for customer experience, operational efficiency, and automation.
2. Engineer solutions with large‑language models (prompting, RAG, fine‑tuning), speech, agentic, and image generation technologies.
3. Apply classical statistical and machine‑learning techniques to complement generative methods.
4. Perform rigorous validation of model performance, error analysis, and data curation or augmentation.
5. Build production‑ready code, integrate versioning, CI/CD, and monitoring workflows.
6. Collaborate with Agile teams, contribute to sprint planning, and foster knowledge sharing.
**Required Skills**
- Python (model building, data pipelines) and ML engineering fundamentals (version control, CI/CD).
- Expertise with LLMs, prompt engineering, retrieval‑augmented generation, and fine‑tuning.
- Experience in speech AI, agentic AI, image generation/interpretation, and classical ML.
- Strong analytical skills, data‑centric mindset, responsible AI awareness.
- Excellent written and verbal communication; fluent in English, with functional French and/or Dutch.
**Required Education & Certifications**
- Master’s degree in a quantitative field (statistics, computer science, engineering) with NLP focus; PhD an advantage.
- Minimum 3 years of practical data‑science experience, preferably within finance (academically robust candidates may be considered).
- Demonstrated ability to manage end‑to‑end AI projects from research to production.