Senior Antifraud Data & Process Analyst

Responsibilities

• Build and maintain dashboards and automated reports on fraud rates, savings, verifications, and key KPIs.
• Create scripts and logic for detecting fake activity and other fraud scenarios e.g., fraudulent orders, promo abuse.
• Analyze recruitment, activation and promo data to spot unusual patterns.
• Integrate new data sources and contribute to cross functional data collaboration.
• Support new data source integration and cross team data collaboration.
• Provide ad hoc support for fraud investigations and strategic reviews.
• Document fraud verification processes end to end, covering all verticals.
• Review and optimize SOPs in collaboration with technical and operational teams Identify inefficiencies or gaps and propose automation or redesign of fraud workflows.
• Support cross team workshops and build visual process maps.
• Define and track process KPIs related to fraud mitigation performance.
• Prepare reports based on available data for management.
• Business analysis on current fraud prevention processes.
• Research and implementation of missing AI/ML fraud detection tools.
• Development of data analytics and machine learning models to detect fraud patterns and anomalies.

Qualifications

• 3-5 years of experience in data analysis and business process analysis, with a strong background in financial, economic security, or risk management sectors.
• Bachelor’s or Master’s degree in a relevant field such as Data Science, Business Analytics, Computer Science, Economics, Mathematics, Statistics, or Engineering.
• Proven experience in advanced data analysis, visualization, and reporting, using tools like Python, R, SQL, Tableau, or Power BI.
• Advanced certifications in data analysis or related fields (e.g., Certified Analytics Professional (CAP), Microsoft Certified: Azure Data Scientist, SAS Certified Data Scientist) are advantageous.
• Basic coursework or understanding of fraud detection, economic crime prevention, and risk management is beneficial.
• Extensive experience in developing and implementing analytical models and strategies to detect and prevent fraud.
• Advanced SQL and Database Management.
• Proficiency in Python or R for Data Analysis.
• Data Visualization Tools (e.g., Tableau, Power BI)
• Google Sheets and Excel, advanced functions and macros.
• Data Mining and Pattern recognition skills.
• Complex Statistical Analysis.
• English C1+

Conditions & Benefits

• Stable salary, official employment.
• Health insurance.
• Hybrid work mode and flexible schedule.
• Relocation package offered for candidates from other regions.
• Access to professional counseling services. including psychological, financial, and legal support.
• Discount club membership.
• Diverse internal training programs.
• Partially or fully payed additional training courses.
• All necessary work equipment.