Data Scientist

Paysafe is a leading payments platform with an extensive track record of serving merchants and consumers in the global entertainment sectors. Its core purpose is to enable businesses and consumers to connect and transact seamlessly through industry-leading capabilities in payment processing, digital wallet, and online cash solutions. With 29 years of online payment experience, an annualized transactional volume of $152 billion in 2024, and approximately 3,000 employees located in 12+ countries, Paysafe connects businesses and consumers across 260 payment types in 48 currencies around the world. Delivered through an integrated platform, Paysafe solutions are geared toward mobile-initiated transactions, real-time analytics and the convergence between brick-and-mortar and online payments. Further information is available at www.paysafe.com. 

Ready to turn data into impact? As a Data Scientist focused on financial crime prevention, you’ll help shape the future of online payments. You’ll work with engineers, analysts, and product managers to design and deploy machine learning solutions at scale—solutions that protect customers, drive innovation, and influence the global payments industry. This is your chance to bring new ideas to life and see them make a real difference.

What you will do:

• Design and implement machine learning models to prevent financial crime
• Bring cutting-edge research into practical, scalable solutions
• Explore new data sources and creative approaches to fraud detection
• Collaborate with operations and product teams to align solutions with business goals
• Own ML systems end-to-end—from data collection to deployment and monitoring
• Ensure quality, performance, and continuous improvement of ML models
• Work closely with IT and product teams to integrate ML into our products

To be successful you need to have:

• BSc in Computer Science, Machine Learning, or related field
• 4+ years of experience in machine learning and applied research
• Strong Python and SQL skills, plus experience with ML frameworks (TensorFlow, PySpark, etc.)
• Hands-on experience deploying ML systems in production
• Familiarity with deep learning applications (NLP, CV, Speech) and graph algorithms
• Experience with cloud platforms (AWS, Azure)
• Excellent communication and collaboration skills
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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.