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Data Scientist – Transaction MonitoringOF-005

ITProposal


Job Location:

Utrecht - Netherlands

Monthly Salary: Not provided by the employer
Posted: 21 June 2026 (30+ days ago)
Application Deadline: 18 September 2026
Vacancies: 1 Vacancy

Job Summary

Location: Utrecht
Duration: ASAP June 2027
Hours: 36 hours per week
Language: English (Mandatory)

Role Overview

We are seeking a Data Scientist with a passion for combating financial crime through data this role you will develop and optimize transaction monitoring models used to detect suspicious activity and identify patterns related to money laundering and terrorist financing. You will work with large-scale datasets and collaborate with business analytics and technology teams to improve detection capabilities and support data-driven decision-making.

Key Responsibilities
  • Develop and enhance transaction monitoring detection rules through data analysis model development and robust coding practices.
  • Analyze customer and transaction data to identify suspicious patterns and emerging risks.
  • Identify and evaluate new data sources to improve model effectiveness.
  • Support the implementation maintenance and continuous improvement of analytical models in production environments.
  • Collaborate with data scientists analysts IT specialists and business stakeholders to ensure consistent methodologies and best practices.
  • Communicate analytical findings and model insights clearly to both technical and non-technical stakeholders.
Required Qualifications
  • Masters degree in Data Science Econometrics Mathematics Statistics Computer Science or a related quantitative field.
  • 35 years of experience in Data Science or Data Analysis preferably working with large datasets.
  • Strong programming skills in Python and PySpark.
  • Experience with Azure Databricks is advantageous.
  • Experience implementing and maintaining analytical models in production environments is preferred.
  • Strong statistical and analytical skills.
  • Excellent verbal and written communication skills in English.
  • Ability to explain complex analytical concepts to business stakeholders.
Preferred Experience & Skills
  • Experience in transaction monitoring financial crime detection AML fraud analytics or related domains.
  • Knowledge of machine learning techniques and model development.
  • Experience working in Agile environments.
  • Strong problem-solving skills and a structured detail-oriented approach.
  • Ability to work effectively in multidisciplinary teams.
Personal Attributes
  • Motivated to contribute to the fight against financial crime.
  • Analytical proactive and results-oriented.
  • Strong collaboration and stakeholder management skills.
  • Comfortable working in a dynamic high-impact environment.