Director Consumer Risk Data Science

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.

As the Director for Consumer Risk Data Sciences at Paysafe, you will play a pivotal role that involves leveraging advanced data analytics, machine learning, and predictive modelling to optimize risk management solutions for consumer in a fast-paced global payments environment. This role will be reporting to the Chief Data and Analytics Officer that requires both strategic and tactical leadership to build on an existing team of analysts and data scientists to drive strategic growth.

Responsibilities

• Lead Consumer Risk ML/AI Strategy: Drive the development and execution of ML/AI strategies to identify, assess, and mitigate consumer-related risks within the payment ecosystem. Address consumer fraud prevention, wallet credit card loading fraud, and alternative payment method fraud.
• Risk Modeling & Advanced Analytics: Develop and deploy advanced machine learning algorithms, statistical models, and predictive analytics to improve risk detection and prevention measures. Utilize risk engines, big data tools and platforms to enhance decision-making capabilities.
• Consumer Risk Strategy and Oversight: Collaborate with external and internal stakeholders to monitor, report, and mitigate Consumer risks across the global payments landscape. Ensure that risk management strategies are aligned with changing market conditions and regulatory guidelines.
• Team Leadership and Development: Lead, mentor, and inspire a high-performing team of data scientists and analysts. Foster a collaborative and innovative environment that encourages continuous learning and growth.
• Cross-functional Collaboration: Work closely with risk, product, engineering, compliance, and operational teams to build scalable risk models and tools. Ensure alignment of risk policies with business objectives and regulatory requirements.
• Regulatory and Compliance Oversight: Ensure that all risk ML practices comply with relevant laws, industry standards, and global regulatory requirements.
• Innovation and Process Improvement: Identify opportunities to innovate and continuously improve risk detection processes, tools, and systems. Stay ahead of industry trends and best practices in risk management.

Qualifications

• At least 10+ years of experience in data science, risk management, or fraud analytics, with a strong background in the global payments industry. 5+ years of leadership experience managing cross-functional teams.
• Exceptional leadership, mentoring, and team management skills. Ability to effectively communicate complex data insights and risk strategies to non-technical stakeholders, including senior executives.
• Strong proficiency in data analytics and modelling tools (e.g., Feedzai, AWS Sagemaker, Python, SQL, Spark etc). Knowledge of application of machine learning, AI, and advanced statistical methods to detect and mitigate risk.
• Strong analytical and problem-solving skills with a focus on actionable outcomes. Ability to balance risk mitigation with business growth and innovation.
• Expertise in risk management, fraud detection, and financial crime prevention.
• Familiarity with global payment systems, e-commerce platforms, and financial technologies.
• Strong understanding of regulatory requirements and industry standards (e.g., PCI DSS, GDPR, PSD2).
• Knowledge of emerging risk trends and technologies in financial services, such as blockchain, digital currencies, and AI-driven risk tools.

Educational Qualification

PhD or Master’s degree in Data Science, Artificial Intelligence, Statistics or a related quantitative field preferred. Strong academic foundation in machine learning, statistical modelling, and data-driven research methodologies is highly desirable.

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.