Lead Data Scientist, AI Engineering
Lead Data Scientist, AI Engineering
Overview Mastercard's AI Centre of Excellence is building the next generation of AI capabilities powered by large-scale transaction data, machine learning, and foundation models. We are transforming how AI solutions are developed by enabling teams to leverage reusable learned intelligence rather than building bespoke feature-engineering pipelines for every use case. We are seeking a Lead Data Scientist, AI Engineering to lead the development of advanced machine learning solutions across domains. This role combines deep expertise in predictive modelling, experimentation, and technical leadership to deliver measurable business impact. What You'll Work On This role focuses on applying machine learning, predictive modelling, and foundation-model representations to solve business problems at scale. Typical use cases include forecasting, propensity modelling, recommendation systems, behavioural analytics, and customer intelligence. While familiarity with Generative AI is beneficial, this is primarily an applied machine learning and data science leadership role rather than a conversational AI, RAG, or agentic systems engineering position. Role / Key Responsibilities Lead the design, development, and deployment of machine learning solutions that solve high-impact business problems. Define modelling approaches, experimentation frameworks, and success metrics for AI initiatives. Apply foundation-model embeddings and modern machine learning techniques to improve model performance and accelerate development. Drive projects from problem definition through model deployment and business impact measurement. Establish robust evaluation frameworks and benchmark new approaches against existing solutions. Partner with business, product, engineering, and analytics teams to identify and prioritise opportunities. Present technical findings and recommendations to stakeholders and senior leadership. Mentor and develop data scientists and AI engineers through technical guidance, reviews, and coaching. Contribute to hiring, capability development, and the long-term technical direction of the AI organisation. All About You All activities involving access to Mastercard assets, information, and networks comes with an inherent risk to the organization and, therefore, it is expected that every person working for, or on behalf of, Mastercard is responsible for information security and must:
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