AML Data Scientist

Paysafe is a global payments platform powering the experience economy, with a strong focus on the iGaming, video gaming, e-commerce, retail, travel and hospitality sectors. With 30 years of expertise in payment technology, Paysafe helps businesses and consumers lift every experience through seamless, secure payment solutions, including card payments, digital wallets such as Skrill, eCash solutions like PaysafeCard, and a suite of local payment methods. With approximately 2,900 employees across 12 countries and annualized transactional volume of $167 billion in 2025, Paysafe connects people and businesses worldwide through innovative digital payment experiences. Further information is available at www.paysafe.com.

As our AML Data Scientist, you'll sit at the center of Global AML Operations, turning billions of transactions, behavioral signals and investigation outcomes into detection logic that actually stops criminal activity. You'll build the models, rules and dashboards that protect millions of customers across our digital wallet, eCash and payment processing products — and you'll see the impact of your work in real investigation outcomes, not just in a report. It's a rare mix of hands-on data science and genuine subject-matter influence, working with modern tooling and some of the sharpest financial crime specialists in the payments industry.

What to expect:

• Analyze large, complex datasets - transactional, behavioral, device, geolocation and investigative - to uncover patterns, anomalies and emerging financial crime risks
• Design, tune and optimize transaction monitoring rules: threshold and percentile analysis, segmentation, false positive reduction and SAR conversion performance
• Partner with our Enterprise Data Science team on AML detection models - feature engineering, validation, performance monitoring and model governance
• Explore where machine learning, network analytics and advanced statistical techniques can push our detection capability further
• Build dashboards, metrics and visualizations that give AML leadership a clear view of risk and operational effectiveness
• Support new product launches and payment flows with transaction-flow analysis and monitoring coverage assessments
• Work alongside typology analysts and investigators to quantify and validate new financial crime trends, mule networks and organized abuse
• Translate AML business needs into technical requirements and partner with AML Risk Systems through testing and deployment

To be successful you need to have:

• A degree in a quantitative field - Data Science, Statistics, Mathematics, Computer Science, Economics, Finance or similar
• Solid experience in data science, advanced analytics, BI, or fraud/risk/financial crime analytics
• Strong SQL and Python, with hands-on statistical modelling, data mining and predictive analytics
• Experience building reporting and dashboards (Power BI, Tableau or similar)
• Comfort working with large, messy datasets to drive real operational decisions
• The ability to explain complex analysis clearly to non-technical stakeholders

Nice to have:

• Background in fintech, payments, banking, e-money or crypto
• Exposure to transaction monitoring, fraud detection or compliance analytics
• Familiarity with Snowflake, Databricks, SAS, Feedzai or network analysis tools
• Working knowledge of AML/CFT regulation, financial crime typologies or model governance

We offer in return:

• The opportunity to write the history of a leading and growing multinational company
• Tailor-made training and ongoing development to help you enhance your skills in the field of online payments
• Multiple career progression opportunities in a dynamic in-house business
• Environment where product expertise, professional and personal commitment are rewarded
• Competitive remuneration and social benefits package (25 days annual paid leave, 4 days paid volunteering time a year through our Paysafe Giving initiative, health insurance, sports card, team events, company discounts, variety of soft skills, business and technical training programs)
• Fun and collaborative working atmosphere
• Flexible working model - we encourage our employees to embrace our flexible working approach. You will be expected to work from home and spend an average of three days a week at our Sofia office as part of our hybrid work model

Are you ready to take your career to the next level? Join our team that is inspired by a unified vision and propelled by passion.
Send your CV in English.
Only shortlisted candidates will be contacted for an interview.


Wondering how our interview process looks like now? Learn more here: https://bit.ly/paysafeinterviews


Equal Employment Opportunity
Paysafe provides equal employment opportunities to all employees, and applicants for employment, and prohibits discrimination of any type with regard to ethnicity, religion, age, sex, national origin, disability status, sexual orientation, gender identity or expression, or any other protected characteristics. This policy applies to all terms and conditions of recruitment and employment. If you need any reasonable adjustments please let us know. We will be happy to help and look forward to hearing from you.