Principal Data Scientist in London

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 3,300 employees located in 12+ countries, Paysafe connects businesses and consumers across 260 payment types in 48 currencies around the world.

As Director, Merchant Risk Data Science, you will play a hands‑on technical leadership role, working with groups of data scientists, driving the design and delivery of next‑generation AI/ML models for merchant risk at Paysafe. Reporting to the Head of Merchant Data Science, you will focus on advanced modelling, applied research, and production delivery, building on existing foundational models to push capability into modern AI techniques. The role is highly technical, requiring deep expertise in advanced machine learning techniques, capable of taking research‑grade ideas (e.g. Transformers, representation learning, graph models) and turning them into real, production‑ready risk solutions across Paysafe’s payment platforms.

Our values and culture are driven by equality, development, social responsibility and wellbeing. If you want to find out more about life at Paysafe, check out our careers page.

How we work: We follow a hybrid working model, spending an average of three days per week at our office location. We are open to this role being based in either our London or Dublin hub. The Dublin office is located in George’s Quay in the heart of Dublin, whilst our London office is in St Paul’s.

The impact you will have:

• Design, prototype, and productionalize advanced AI/ML models for merchant fraud, abuse, chargebacks, and anomalous behaviour.
• Lead the adoption of modern modelling techniques, including: Transformers and sequence models, Representation learning & embeddings, Autoencoders and anomaly detection, Graph / network‑based models, Semi‑supervised and weakly supervised learning.
• Own the end‑to‑end model lifecycle: problem framing, feature representation, model development, validation, deployment, monitoring, and iteration.
• Partner closely with Risk Strategy, Operation, MLOps and Data Engineering to ensure models are scalable, explainable, and production‑ready in real‑time or near‑real‑time environments (e.g. AWS SageMaker).
• Act as a technical authority for advanced AI in merchant risk, influencing architecture, tooling, and long‑term modelling strategy.
• Balance innovation with model governance, regulatory expectations, and risk controls, without limiting technical ambition.
• Partner with Data Engineering to shape: Data requirements for advanced models, Feature stores and pipelines, The evolution of merchant risk data infrastructure.
• Act as a bridge between research, engineering, and business, ensuring models are both technically strong and operationally impactful.

What we’re looking for – Experience & Profile:

• 10+ years in data science / advanced analytics, with strong hands‑on delivery experience.
• Demonstrated experience working with modern AI/ML techniques beyond tree‑based models.
• Proven ability to take research concepts into production.
• Experience in payments, fraud, or risk is valuable but not mandatory.

What we’re looking for – Technical Skills:

• Expert‑level Python and modern ML tooling.
• Strong hands‑on experience with: Transformers, LSTM / sequence models, Representation learning & embeddings, Autoencoders & anomaly detection, Graph / network modelling.
• Experience operationalising models on AWS SageMaker (or equivalent).
• Strong understanding of model evaluation, explainability, and monitoring in high‑risk environments.

What we’re looking for – Education:

• Advanced degree (Master’s or PhD) in Statistics, Mathematics, Data Science, AI/ML, or a related field. PhD or equivalent advanced industry experience preferred.

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.
• Dedicated 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 3pm finish every Friday.
• Private health insurance (pre‑existing conditions included) & dental insurance, income protection, life assurance and more.

What to expect next:

• Phone screen with Talent Acquisition.
• Video interview with the Hiring Manager.
• Technical interview with team member.
• In‑person interview with CDO and Talent Acquisition.

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.