Lead Data Scientist in London

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 an annualized transactional volume of $167 billion in 2025, Paysafe connects people and businesses worldwide through innovative digital payment experiences.

We are looking for a Lead Data Scientist to join our Consumer Risk Data Science team, focused on machine learning modelling in fraud detection and financial crime prevention within the payment ecosystem. This role combines deep hands‑on modelling expertise with technical leadership and domain ownership. You will lead the design and development of advanced machine‑learning solutions, set modelling standards, and drive best practices across the team. You will play a key role in shaping the evolution of our modelling capabilities, working with large‑scale transactional data and collaborating closely with Engineering, Product, and Risk teams to deliver scalable, high‑impact solutions.

Key responsibilities:

• Lead the development and delivery of end‑to‑end data science solutions, from problem definition through model development to production deployment.
• Own and drive modelling approaches for key fraud / financial crime use cases across the customer lifecycle.
• Build and optimize machine learning models, selecting and guiding the use of appropriate techniques based on data and problem context.
• Define and enforce best practices in feature engineering, model validation, and experimentation frameworks.
• Oversee model productionisation, ensuring alignment with MLOps standards and scalable deployment patterns.
• Drive model performance monitoring, governance, and continuous improvement across the portfolio.
• Collaborate with cross‑functional teams to ensure effective integration of models into production systems and workflows.
• Act as a subject‑matter expert (SME) in fraud modelling and advanced analytics, providing guidance to stakeholders and team members.
• Mentor and develop data scientists, and where applicable, provide line management and support team growth.
• Contribute to technical strategy, tooling, and long‑term evolution of data science capabilities within the team.

Required skills and experience:

• 7–10+ years of experience in data science / machine learning roles.
• Strong proficiency in Python (NumPy, Pandas, Scikit‑learn, etc.).
• Proven track record of developing and deploying ML models in production environments.
• Strong hands‑on experience with feature engineering at scale, model validation frameworks (including time‑based / OOT approaches), supervised and unsupervised learning techniques.
• Experience working with cloud technology stacks (AWS, Azure, etc.).
• Demonstrated ability to lead complex data science projects and influence technical direction.
• Strong communication skills, with the ability to explain complex analytical concepts to non‑technical stakeholders.

Strongly preferred:

• Experience in fraud, risk, or payments domain.
• Experience with real‑time or near real‑time modelling environments.
• Exposure to graph‑based modelling, deep learning, or advanced ML techniques (Sequential modelling, representation learning, transformer, etc.).

Education:

• Bachelor’s or Master’s degree in a quantitative field (e.g., Computer Science, Mathematics, Statistics, Engineering). Advanced degree is a plus.

A snippet of what you’ll get in return:

• Flexible working hours.
• Option to buy or sell your holiday and carry over up to 5 days into the next year.
• Social events on our roof top terrace with views onto St Pauls Cathedral.
• Fully equipped facilities include showers, hairdryers and straighteners and fresh towels.
• Free breakfast, fresh fruit and snacks.
• Dedicating wellbeing room.
• Enhanced paid family policies.
• £50 into each wallet upon joining.
• Discounts on memberships via vitality including gyms, leisure centres, yoga/Pilates across the country.
• Support purchasing Apple and LG products via Stormfront technology.
• Join our six employee‑led equality communities.
• Four paid charity days.
• Summer hours during June, July and August with a 3 pm finish every Friday.
• Private health insurance (pre‑existing conditions included) & dental insurance, income protection, life assurance and more.

Paysafe is an equal opportunity employer. We value diversity and are committed to providing a work environment of mutual respect to everyone without regard to race, color, religion, national origin, age, gender identity or expression, or any other characteristic protected by applicable laws, regulations and ordinances.