Data Analyst – Anti-Financial Crime / Banking (f/m/x)
In short
Data Analyst for a long-term project in financial services (Gdynia). Responsibilities include data analysis, quality improvement, Power BI reporting, and collaborating on solutions. Requires SQL, Python, R, Java, Scala, Power BI, and financial crime domain experience (AML, KYC).
Keywords
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 | 2026-08-07 |
| Expires | 2026-11-05 |
| Source |
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