Job Title: Senior Data Scientist — Financial Crime & Credit Risk Analytics

Location: Tartu or Tallinn, Estonia
Work Arrangement: Hybrid / Remote
Employment Type: Full-Time
Department: Advanced Analytics & Risk Intelligence

About the Company

We are an innovative fintech organisation developing intelligent financial products and risk management solutions for European markets. Our business uses advanced analytics, statistical modelling, and machine learning to strengthen fraud prevention, improve credit assessment, and support responsible financial decision-making.

Role Overview

We are seeking a Senior Data Scientist to lead analytical initiatives across fraud detection, credit risk modelling, and financial risk intelligence. This role combines advanced statistical expertise, predictive analytics, and business collaboration to identify emerging risks and improve the quality of financial decisions.

You will work closely with data science, engineering, compliance, fraud operations, and credit risk teams to develop analytical solutions that deliver measurable business outcomes. The successful candidate will also help establish modelling standards, mentor colleagues, and communicate complex insights to senior stakeholders.

Key Responsibilities

• Lead the development of advanced analytical models for fraud detection, credit scoring, default prediction, and financial risk segmentation.
• Design statistical experiments and conduct in-depth analyses of financial transactions, customer behaviour, and lending performance.
• Develop and validate classification, regression, time-series, and anomaly detection models.
• Identify emerging fraud trends, credit deterioration patterns, and portfolio risk drivers.
• Apply feature engineering, model selection, and advanced statistical techniques to improve predictive performance.
• Evaluate model stability, calibration, explainability, and business effectiveness.
• Conduct portfolio analysis, customer segmentation, and scenario analysis to support strategic decisions.
• Translate complex analytical findings into clear recommendations for management and operational teams.
• Partner with engineers to deploy analytical models and integrate predictive insights into business workflows.
• Establish best practices for reproducible analysis, model documentation, validation, and monitoring.
• Mentor junior data scientists and review analytical methodologies and technical outputs.
• Support responsible AI initiatives, data governance, and compliance with applicable financial regulations and data protection requirements.

Requirements and Qualifications

• Master’s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related quantitative discipline; equivalent experience may be considered.
• At least 5 years of professional experience in data science, predictive analytics, financial risk, or a related quantitative field.
• Advanced proficiency in Python and SQL.
• Strong knowledge of statistical modelling, machine learning, hypothesis testing, and predictive analytics.
• Experience developing models for fraud prevention, credit scoring, financial crime analytics, or risk management.
• Expertise in model evaluation, calibration, feature engineering, and analytical validation.
• Experience with large datasets, data visualisation, and analytical reporting tools.
• Familiarity with model explainability methods such as SHAP and with responsible model governance.
• Experience collaborating with software engineers to operationalise analytical models is desirable.
• Demonstrated ability to lead analytical projects, mentor colleagues, and communicate with senior stakeholders.
• Strong judgement, attention to detail, and a commitment to evidence-based decision-making.

What We Offer

• Competitive salary reflecting seniority and technical expertise.
• Flexible working arrangements, subject to business requirements.
• Opportunity to lead high-impact analytics projects across fraud and credit risk.
• Access to modern data infrastructure and advanced analytical technologies.
• Professional development and opportunities to influence data science strategy.
• A collaborative international team and a supportive technical environment.
• Career progression and opportunities to contribute to the development of financial risk capabilities.

Application Instructions

Please submit an up-to-date CV outlining your experience in advanced analytics, credit risk, fraud detection, and predictive modelling. Candidates should highlight significant projects, analytical methods used, measurable outcomes, and experience communicating insights to business stakeholders.

Lead data-driven innovation across fraud prevention and credit risk, turning advanced analytics into better financial decisions.

Are you interested in this position?

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

#JobsHubEstonia #GlobalRecruitment
#CareerOpportunities #HiringNow
#JobSeekersNetwork #EstoniaJobs
#RecruitmentServices #EmploymentPortal.