At a Glance
- Tasks: Lead innovative risk data science strategies to combat consumer fraud in global payments.
- Company: Join Paysafe, a leading payments platform with a global reach.
- Benefits: Enjoy competitive pay, flexible work, and extensive training opportunities.
- Other info: Collaborative culture with multiple career progression opportunities.
- Why this job: Make a real impact in the fast-paced world of digital payments.
- Qualifications: 10+ years in data science and risk management, with strong leadership skills.
The predicted salary is between 48000 - 72000 € per year.
About Paysafe
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.
As the Director Risk Data Science 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 consumers in a fast-paced global payments environment. This role 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.
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.
Director Risk Data Science in London employer: Paysafe
At Paysafe, we pride ourselves on being a leading payments platform that not only drives innovation in the global entertainment sector but also fosters a vibrant work culture. As a Director of Risk Data Science, you will benefit from tailored training, multiple career progression opportunities, and a flexible working model that promotes work-life balance, all while being part of a collaborative team dedicated to making a meaningful impact in the payments industry.
StudySmarter Expert Advice🤫
We think this is how you could land Director Risk Data Science in London
✨Tip Number 1
Network like a pro! Reach out to your connections in the payments industry and let them know you're on the lookout for opportunities. A personal recommendation can go a long way in landing that interview.
✨Tip Number 2
Prepare for those interviews by brushing up on your knowledge of machine learning and risk management. Be ready to discuss how you've used data analytics to tackle real-world problems, especially in the payments sector.
✨Tip Number 3
Showcase your leadership skills! Be prepared to share examples of how you've mentored teams or driven strategic initiatives. Paysafe values collaboration, so highlight your ability to work cross-functionally.
✨Tip Number 4
Don't forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you're genuinely interested in joining the Paysafe team.
We think you need these skills to ace Director Risk Data Science in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Director Risk Data Science role. Highlight your experience in data science, risk management, and leadership. Use keywords from the job description to show we’re on the same page!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for risk management and how your skills align with our mission at Paysafe. Keep it concise but impactful – we want to see your personality!
Showcase Your Achievements:Don’t just list your responsibilities; showcase your achievements! Use metrics and examples to demonstrate how you’ve made a difference in previous roles. We love seeing results!
Apply Through Our Website:We encourage you to apply through our website for a smoother process. It helps us keep track of applications and ensures you don’t miss out on any important updates. Let’s get started on this journey together!
How to prepare for a job interview at Paysafe
✨Know Your Data Science Inside Out
As a Director of Risk Data Science, you’ll need to showcase your expertise in data analytics and machine learning. Brush up on the latest algorithms and tools like Python and SQL, and be ready to discuss how you've applied them in real-world scenarios, especially in risk management.
✨Demonstrate Leadership Skills
This role requires strong leadership abilities. Prepare examples of how you've successfully led teams in the past, mentored junior analysts, and fostered a collaborative environment. Highlight your experience in managing cross-functional teams and driving strategic initiatives.
✨Understand the Payment Landscape
Familiarise yourself with the global payments industry, including current trends and regulatory requirements. Be prepared to discuss how you would address consumer fraud and risk management in this context, showing that you can align risk strategies with business objectives.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving skills in real-time situations. Think about potential risks in the payment ecosystem and how you would mitigate them using advanced analytics. Practising these scenarios will help you articulate your thought process clearly during the interview.
