Data Scientist AI
Stichting Achmea Rechtsbijstand
Tilburg, Netherlands
8 days ago
Role details
Contract type
Permanent contract Employment type
Full-time (> 32 hours) Working hours
Regular working hours Languages
EnglishJob location
Tilburg, Netherlands
Tech stack
Artificial Intelligence
Amazon Web Services (AWS)
Computer Vision
Azure
ETL
Distributed Systems
Python
Machine Learning
TensorFlow
SQL Databases
Data Processing
Google Cloud Platform
PyTorch
Model Validation
Generative AI
Scikit Learn
Data Pipelines
Job description
Tilburg Als Data Scientist AI bij Stichting Achmea Rechtsbijstand ontwikkel, train en implementeer je AI/ML- en NLP-oplossingen voor juridische data, van businessvraag en POC tot productie, met focus op modelkwaliteit, uitlegbaarheid, monitoring en Responsible AI. Direct solliciteren Neem contact op, Develop and deploy AI-driven analytics and machine learning solutions that improve decision-making, automate processes, and create measurable business impact., * Design, build, and validate machine learning and statistical models for prediction, classification, recommendation, or optimization.
- Collect, clean, and transform structured and unstructured data; define features and data quality checks.
- Run experiments (A/B tests, offline evaluation), interpret results, and communicate insights to stakeholders.
- Deploy models to production with monitoring, drift detection, and iterative performance improvements.
- Collaborate with product, engineering, and domain teams to translate business needs into data science deliverables.
- Create clear documentation for datasets, models, assumptions, and reproducible workflows.
Requirements
- Strong foundation in statistics, machine learning, and model evaluation.
- Proficiency in Python and common ML libraries (e.g., scikit-learn, PyTorch, TensorFlow).
- SQL and data wrangling skills; experience with data pipelines and ETL processes.
- Experience with model deployment and MLOps practices (APIs, CI/CD, monitoring).
- Ability to communicate complex findings clearly to technical and non-technical audiences.
Preferred Qualifications
- Experience with cloud platforms (AWS, GCP, Azure) and distributed computing (e.g., Spark).
- Knowledge of NLP, computer vision, or generative AI, depending on domain needs.