Senior Data Scientist - Predictive Models
Sector: Banking
Location: Brussels
Contract length: 14 months
Estimated daily rate (EUR): 620 - 740
Languages: English · Dutch or French
Estimated daily rates are Rivant market estimates for guidance — not a client rate card.
Role details
Start date: 2026-10-26
Duration: 14 months
Extension possible: Not specified
Education: Master's degree or higher in a quantitative field (statistics, mathematics, computer science), or equivalent substantial data-science experience
Location detail: Brussels (5 min walk from Central Station) - 50% on site / 50% homeworking. Remote/telework from Belgium only
About the role
A major Belgian bank in Brussels needs a Senior Data Scientist on the Predictive Models team. You build and deploy responsible AI models that make customer and employee campaigns more relevant — capturing business needs, designing experiments, and turning model output into clear advice for business owners.
Responsibilities
- Build responsible AI models that improve campaign reach and relevance
- Design feasibility analyses, target-group models and impact tests with business stakeholders
- Deliver customer-journey and next-best-action models for marketing campaigns
- Operationalize LLM classification, RAG and summarization pipelines with guardrails
- Track experiments and promote models via MLflow / CI-CD
- Advise business owners on how to use model outputs in live campaigns
Business experience
| Skill | Level | Priority |
|---|---|---|
| Capture business needs for marketing / customer-journey campaigns and advise on model usage | Not specified | Mandatory |
| Customer journey modeling (e.g. next best action) for campaign targeting | Not specified | Mandatory |
| Present technical concepts as clear, actionable insights to non-technical stakeholders | Not specified | Mandatory |
Functional experience
| Skill | Level | Priority |
|---|---|---|
| At least 5 years of relevant data-science experience | ≥5 years | Mandatory |
| Build pipelines that clean/structure web analytics and use LLMs to detect customer intent | Not specified | Mandatory |
| Develop and deploy automated summarization models (LLMs or traditional NLP) | Not specified | Mandatory |
| Monitor and deploy AI models in production with responsible-AI guidelines (e.g. explainability) | Not specified | Mandatory |
Technical experience
| Skill | Level | Priority |
|---|---|---|
| Expert Python data-science stack (scikit-learn, transformers, PyTorch, TensorFlow) | Not specified | Mandatory |
| Fine-tune, evaluate and operationalize LLMs and embedding models for production marketing use | Not specified | Mandatory |
| Statistical methods, experiment design, traditional ML and deep learning | Not specified | Mandatory |
| LLMs for text classification, RAG, interpretability, guardrails and validation | Not specified | Mandatory |
| MLflow for experiment tracking, model versioning and CI/CD in AI/ML workflows | Not specified | Mandatory |
| git, bash and SQL | Not specified | Mandatory |
| Active learning, uplift modeling, Marketing Mix Modeling / optimization under constraints | Not specified | Preferable |
| SAS and Streamlit | Not specified | Preferable |
Language requirements
English · Dutch or French
| Language | Speaking | Reading | Writing | Mandatory |
|---|---|---|---|---|
| English | Fluent | Fluent | Fluent | Yes |
| Dutch | Fluent | Fluent | Fluent | No |
| French | Fluent | Fluent | Fluent | No |
Soft skills
- Take ownership and drive projects end-to-end with minimal guidance
- Translate data insights into actionable business recommendations
- Clear, concise communication with business owners
- Team player; proactive and result-driven; analytical problem-solving
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