A sophisticated financial technology business in Estonia is seeking a Fintech Financial Crime Data Analyst to strengthen its ability to identify unusual financial activity through advanced data analysis and intelligent monitoring.

This position combines financial-crime knowledge with analytical expertise. You will work closely with AML, compliance, risk, engineering, and data teams to transform transaction and customer information into meaningful risk intelligence.

Your Role

You will analyse large and complex datasets to identify patterns, investigate anomalies, improve monitoring effectiveness, and provide analytical insight that supports financial-crime prevention.

Key Responsibilities

• Analyse transaction, customer, account, and behavioural datasets to identify unusual patterns.
• Develop analytical approaches for detecting potential financial-crime risks.
• Support the design and optimisation of transaction-monitoring scenarios and risk indicators.
• Investigate data-driven trends across transaction activity and customer behaviour.
• Build recurring analytical reports and dashboards for compliance and risk teams.
• Work with data engineers to improve data availability, quality, and consistency.
• Validate monitoring rules and assess their performance using historical and current data.
• Identify false-positive patterns and recommend opportunities for improved analytical precision.
• Support investigations by providing structured data analysis and contextual insights.
• Develop statistical and analytical methods for identifying emerging risk patterns.
• Collaborate with compliance specialists to translate analytical findings into practical controls.
• Maintain clear documentation of methodologies, assumptions, findings, and analytical outputs.

Candidate Profile

• 4+ years of experience in data analytics, financial crime analytics, AML, fraud analytics, banking, payments, or fintech.
• Strong SQL and Python or comparable analytical-programming skills.
• Excellent understanding of data analysis, statistical concepts, and visualisation.
• Experience working with large transactional or customer datasets.
• Understanding of AML, fraud, transaction monitoring, or financial-risk concepts.
• Strong investigative mindset and attention to detail.
• Ability to communicate technical findings clearly to non-technical stakeholders.

Analytical Environment

SQL, Python, cloud data platforms, BI and visualisation tools, transaction-monitoring systems, data warehouses, customer-risk platforms, automated reporting, and analytical pipelines.

Why This Opportunity

You will work directly with the data underpinning financial-crime controls and help develop more intelligent, evidence-based approaches to identifying financial risk.

Ideal Candidate: A highly analytical professional who can combine technical data skills with financial-crime knowledge and turn complex transaction data into clear, actionable intelligence.

Are you interested in this position?

Apply by clicking on the “Apply Now” Button below!

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