Data Scientist
Role details
Job location
Tech stack
Job description
We're looking for a hands-on Data Scientist to join a project focused on developing advanced fraud detection and anti-money laundering (AML) analytics for one of our fintech clients. The goal is to analyze large amounts of transaction data, detect anomalies, and help shape intelligent solutions that make digital payments safer across Europe.
What will you do?
- Explore and analyze financial data to identify patterns and suspicious behaviors.
- Build and test models using statistical and machine-learning techniques.
- Collaborate with fraud specialists and product managers in shaping data-driven solutions.
- Prototype and validate approaches using real datasets.
Requirements
Do you have experience in Python?, * Strong background in math, statistics, and exploratory data analysis.
- Solid programming skills for data and backend development (Python, Java, or similar).
- Experience with core ML algorithms such as regression, decision trees, or Naïve Bayes.
- Understanding of supervised vs. unsupervised learning and model evaluation.
- Knowledge of data pipelines, data storage, and infrastructure automation.
- Familiarity with model interpretability and explainability.
- Ability to work independently in a discovery-phase environment.
- English fluency.
Nice to have:
- Experience in fraud detection or AML systems.
- Knowledge of tools like FCRM, NICE Actimize, Pega, or RiskShield.
- CI/CD or MLOps exposure.
- Interest in prompt engineering.
Benefits & conditions
- 1 year contract (B2C or B2B) with possibility for extension
- Full-time work (no part time options)
- Hybrid working policy (2 days per week in the cleint's Utrecht office)
- Eligibility to work in the Netherlands (no visa sponsorship provided)
- PTO available
- Salary received in USD
Our values
We are a company that seeks the best for both our employees and clients, reaching beyond expectations in turning dreams into reality. Our way of working is rooted in our core values (Integrity, Excellence, Proactivity, Innovation, and People), with an expectation that our future colleagues will make these their second nature in their everyday work and life. We don't ask for perfection, but we do appreciate people motivated to better themselves in every conceivable aspect.
