Senior Data Scientist, Payments Foundation Models

Job Description

What it's all about - 

The Payments Foundation Models team is a new, high-impact initiative within Visa’s Data Science organisation. Based in Cambridge, UK, and working closely with global Visa engineering and product teams, the group’s mission is to build the next generation of payments-focused foundation AI models. These models will power a range of premium Risk and Identity Solutions (RaIS) products, such as fraud scores, with the goal of generating more than 100M dollars in new revenue by FY2030 and may be extended into other domains such as credit risk modelling or agentic commerce personalization.

In your role as Senior Data Scientist – Payments Foundation Models you will help us achieve our goals and deliver success on behalf of our customers by:

• Developing, training, evaluating, documenting and disseminating Payments Foundation Models for use in data science and AI projects across Visa.
• Collaborating across the organization with engineering, data science, research, product and commercial teams to improve the quality, adoption and real-world impact of our models.
• This is a hands-on technical role in the Individual Contributor track at the Consultant or Manager level, with scope to influence data science standards and practices while working on high-impact, Visa-scale systems.

Responsibilities:

We hire people with a willingness to adapt to a variable role, so along with the key responsibilities below, we ask for ownership of any other duties as required.

• Collaborating with Product Managers & other members of the team to align on the highest value items to work on
• Coordinating work across multiple teams & when needed, taking on additional “tech lead” responsibilities for driving initiatives to completion.
• Identifying risks and testing assumptions before development
• End-to-end processing and modelling of large data sets
• Training deep learning models utilizing self-supervised training, supervised fine-tuning or adaptation approaches.
• Ensuring new deep learning models successfully navigate model risk management processes, ensuring high quality documentation exists alongside analytics products (reports, presentations, visualizations)
• Leading the deployment and maintenance of statistical models and algorithms
• Collaborating with data engineers to identify and implement improvements to tooling.
• Enabling both technical and non-technical colleagues by effectively communicating insights learnt during data science work
• Evangelizing on the benefits of deep learning models within Visa
• Recruiting for Data Scientists within the team
• Improving team processes and providing input to future team strategy
• Mentoring more junior members of the team as well as managing and prioritising their workload to ensure high-quality output.
• Developing a solid understanding of the fraud and financial crime industries

This is a hybrid position. Expectation of days in the office will be confirmed by your Hiring Manager. ​

Qualifications

What we'd like from you - 

Preferred Qualifications:



Advanced degree in Data Science, Computer Science, Physics, Mathematics, or related field.

Strong background in machine learning, statistical modeling, and data engineering.

Enthusiasm for bringing cutting-edge deep learning models into production at Visa-wide scales.

Practical experience managing large-scale datasets and conducting end-to-end analytics projects.

Proficiency with programming languages such as Python or R, and familiarity with SQL and big data tools.

Technical and analytical skills with the ability to pick up new technologies and concepts quickly.

Problem solving skills (especially in data-centric applications).

Strong, clear, concise written and verbal communication skills.

Ability to manage and prioritise personal workload

Excellent communication skills for technical and non-technical stakeholders.

Proven ability to lead cross-functional projects and mentor junior team members.

Ph.D. or other postgraduate level qualification with good mathematical background and knowledge of statistics

Experience with fraud detection, risk analytics, or financial crime prevention.

Experience developing models within a model risk management framework.

Experience with version control software and workflows (e.g. git)

Experience with PyTorch or another deep learning framework

Familiarity with the training and serving of artificial neural networks

Subject matter expertise in the banking and payments industry.

Additional Information

Visa is an EEO Employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, sexual orientation, gender identity, disability or protected veteran status. Visa will also consider for employment qualified applicants with criminal histories in a manner consistent with EEOC guidelines and applicable local law.