- Company Name
- NORRIQ Financial Services
- Job Title
- Data Scientist - Banking
- Job Description
-
**Job Title**: Data Scientist – Banking
**Role Summary**:
Design, develop, and implement AI, machine‑learning, and generative‑AI solutions for banks and financial institutions. Conduct data‑driven analysis, build models, and deliver insights that support senior stakeholders and drive business outcomes.
**Expectations**:
- Develop end‑to‑end AI/ML pipelines for complex financial use cases.
- Maintain reproducible, production‑grade code with MLOps practices.
- Communicate findings and recommendations to senior management.
- Collaborate cross‑functionally with data engineers, analysts, and developers.
**Key Responsibilities**:
- Build and deploy ML and generative AI models using Python, scikit‑learn, and deep‑learning frameworks.
- Perform exploratory data analysis and create dashboards/visualizations.
- Draft Jupyter notebooks for experimentation and documentation.
- Apply generative AI techniques (prompt engineering, retrieval‑augmented generation, fine‑tuning, speech‑to‑text, agentic apps, image generation & interpretation).
- Apply predictive ML and classical approaches to financial datasets.
- Use GitLab, DVC, and MLOps tooling to manage model versioning, reproducibility, and performance.
- Present analytical insights and actionable recommendations to senior leadership.
- Provide technical guidance on data‑science and AI best practices.
- Contribute to an internal Center of Excellence by sharing knowledge and supporting proposal writing.
- Stay current with emerging AI frameworks (LangChain, Haystack, etc.).
**Required Skills**:
- Proficiency in Python, scikit‑learn, deep‑learning libraries (TensorFlow/PyTorch).
- Experience with MLOps tools (GitLab, DVC, ML‑flow, or equivalent).
- Strong analytical and statistical skills.
- Knowledge of generative AI methods (prompt engineering, RAG, fine‑tuning).
- Ability to build dashboards/visualizations (Tableau, Power BI, or Python‑based).
- Excellent written and verbal communication, ability to present to non‑technical stakeholders.
- Fluency in English; conversational Dutch or French; basic knowledge of the other language.
**Required Education & Certifications**:
- Bachelor’s or Master’s degree in Computer Science, Data Analytics, Statistics, or a related quantitative field.
- Relevant certifications in data science, machine learning, or AI (e.g., TensorFlow Developer, AWS AI/ML Specialty) are a plus.