Data Analyst – Anti-Financial Crime / Banking (f/m/x)
In short
Data Analyst for financial services sector project. Responsibilities include data analysis, quality improvement, Power BI reporting, data modeling, and stakeholder collaboration. Requires SQL, Python/R/Java/Scala, Power BI, and financial crime domain experience.
AI-written summary based on the listing content.
We are looking for an experienced Data Analyst to join a long-term project within the financial services sector. In this role, you will support data-driven initiatives by delivering high-quality analytics, improving data quality, and collaborating with cross-functional teams to implement business-critical solutions.
If you thrive in a fast-paced environment, enjoy solving complex data challenges, and have experience working with financial crime domains, we'd love to hear from you.
Your responsibilities
- Perform data analysis to support business and regulatory initiatives.
- Contribute to data quality improvements and data management activities.
- Design and develop reports and dashboards using Power BI.
- Build and maintain simple data models.
- Collaborate with business and technical stakeholders to deliver data-driven solutions.
- Support data migration and integration initiatives where required.
- Ensure high standards of data accuracy, consistency, and governance.
Our requirements
- Proven experience in Data Management, Data Quality, Data Analytics, or a related field, preferably within the financial services industry.
- Strong SQL skills and hands-on experience with Python, R, Java, and Scala.
- Understanding of data taxonomy and the ability to design simple data models.
- Practical experience with Power BI.
- Experience in Financial Crime domains, including AML, KYC, Transaction Monitoring, or Sanctions.
- Strong stakeholder management and communication skills, with the ability to work effectively across both business and technical teams.
- Excellent analytical and problem-solving abilities with a strong attention to detail.
- Ability to adapt to changing priorities in a dynamic project environment.
- Self-driven, well-organised, and capable of working both independently and collaboratively.
- Professional proficiency in English (written and spoken).
Optional
- Experience with Data Governance frameworks and best practices.
- Previous involvement in data migration or system integration projects.
| Published | 2026-10-26 |
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