Data & AI Senior Product Specialist

Salary: £60,000 - 100,000 per year

Requirements:

• We are looking for experience in data and AI product management, data science, or a related field within Financial Services, FinTech, Insurance, or other regulated industries.
• We require a bachelors degree in Data Science, Technology, Mathematics, Statistics, Business Administration, or equivalent work experience; a masters degree or PhD is preferred.
• We expect proven experience building and commercialising data-driven, advanced analytics, AI, and ML products using multiple data sources, including payments, card transactions, macroeconomic, and syndicated data.
• We need experience in two or more of the following areas: forecasting and predictive analytics, self-service reporting, early warning systems, customer segmentation and scoring, credit risk insights, or personalisation.
• We seek a strong understanding of AI and data science techniques, including statistical modelling, logistic regression, NLP, LLMs, Generative AI, and Agentic AI.
• We require a strong track record of applying Agile product development methodologies.
• We value a customer-centric mindset and a proven ability to build trusted relationships and deliver business value.
• We are looking for a highly collaborative approach and experience working effectively across cross-functional teams and external partners.
• We expect a results-oriented mindset, strong ownership, and the ability to deliver high-quality outcomes against demanding timelines.
• We require experience with enterprise business intelligence platforms such as PowerBI, Qlik Sense, Tableau, or similar.
• We expect hands-on familiarity with scalable cloud-based data science platforms such as AWS, Databricks, and Microsoft Azure.
• We need a basic understanding of data ingestion APIs, data flows, analytics tech stack, and data platform architecture.
• Nice to have: programming skills in Python and SQL, with experience processing and analysing large-scale datasets.

Responsibilities:

• We contribute to the Data & Insights strategy by driving value from ideation through launch, scaling, and commercialisation of data-driven products and services.
• We identify high-value data and AI-led opportunities that address customer pain points and create new revenue-generating services across the UK payments ecosystem.
• We work closely with cross-functional teams, including Engineering, Data Science, and Commercial, to deliver our data and insights product strategy, coordinate end-to-end product development using Agile methodologies, and develop market and customer outreach documentation.
• We drive the development of new data solutions through Mastercards Studio framework by defining target audiences, validating customer needs, quantifying market opportunities, and developing business cases and pricing strategies.
• We define, prioritise, and deliver data product roadmaps using Agile methodologies.
• We present data and AI-led products to internal senior stakeholders and customers, translating complex technical concepts and data science models into clear customer benefits and business value.
• We act as a subject matter expert and advocate for Data & AI internally and externally.
• We support go-to-market activities, including customer engagement, commercialisation plans, partnership opportunities, and distribution strategies.
• We drive product documentation, requirements gathering, delivery governance, and project management best practices.

Technologies:

• Agentic AI
• AI
• AWS
• Azure
• Business Intelligence
• Cloud
• Databricks
• Support
• Network
• Python
• Qlik
• SQL
• Tableau
• Security

More:

We are Mastercard, a global technology company in the payments industry, and through our company Vocalink we design, build, and operate industry-leading bank account-based payment systems. Our technology powers the UKs real-time and account-to-account payments, settlements, direct debit systems, and a network of nearly 70,000 ATMs. Within our Data & Insights function, we deliver payment reporting and customised analytics to internal stakeholders and external customers, and this full-time role sits within our AI & Data profession.

last updated 36 week of 2026