Use Artificial Intelligence to Make Financial Risk Decisions Smarter

We are seeking an AI Risk Intelligence Specialist to develop data-driven capabilities for identifying financial risk, unusual behaviour, fraud patterns, and emerging threats across digital financial products.

This is a forward-looking position combining artificial intelligence, machine learning, financial risk, behavioural analytics, and fintech. You will work with multidisciplinary teams to turn complex data into actionable intelligence.

The Challenge

Modern financial platforms generate enormous volumes of behavioural and transactional information. The opportunity is to move beyond static rules and develop intelligent systems capable of identifying patterns that traditional monitoring approaches may overlook.

Key Responsibilities

• Analyse transaction, behavioural, customer, and operational data to identify emerging risk patterns.
• Support the development of machine-learning models for fraud and financial-risk detection.
• Design features and analytical approaches for behavioural risk scoring.
• Evaluate model performance, precision, recall, false-positive rates, and operational impact.
• Work with data scientists and engineers to productionise risk models.
• Investigate unusual patterns and translate analytical findings into practical risk controls.
• Develop dashboards and analytical tools for risk and operational teams.
• Monitor model performance and identify potential model drift.
• Assist in developing explainable and auditable AI approaches for financial decision-making.
• Collaborate with compliance, fraud, product, engineering, and data teams.
• Research emerging fraud techniques, technological threats, and AI applications within financial services.
• Contribute to responsible AI practices, model governance, and appropriate data-management standards.

Candidate Profile

• 4+ years of experience in data science, fraud analytics, financial risk, machine learning, or related fields.
• Strong Python and SQL skills.
• Experience with statistical modelling and machine-learning techniques.
• Understanding of classification, anomaly detection, behavioural modelling, and predictive analytics.
• Experience working with large transactional or customer datasets.
• Familiarity with tools such as scikit-learn, pandas, PyTorch, TensorFlow, or comparable technologies.
• Strong analytical thinking and ability to communicate technical findings clearly.
• Experience in fintech, payments, banking, fraud prevention, or financial risk is strongly preferred.
• Understanding of model governance, explainability, and data-quality considerations is an advantage.

Why This Opportunity

This role goes beyond conventional analytics. You will help build intelligent risk capabilities capable of adapting to changing financial behaviour and increasingly sophisticated threats.

For a professional interested in the intersection of AI and financial technology, this is an opportunity to make a direct impact on the security, reliability, and scalability of next-generation fintech services in Estonia.