Top Tech Jobs & Startup Jobs in Dublin

Designs data-driven digital products, prototypes, dashboards, web and mobile applications, chatbots, and voice interfaces using human-centered design, Lean UX, and Design Thinking. Collaborates with users, product managers, technology teams, marketing, and regional stakeholders to develop MVPs, define design patterns, conduct workshops, and optimize business and user outcomes for global B2B and B2B2C experiences.

Leads delivery for an AI Foundations and Agents engineering team, managing planning, execution, release coordination, dependencies, risks, Agile ceremonies, and operational readiness. Partners with product, engineering, architecture, security, and platform stakeholders to improve delivery predictability, engineering effectiveness, reporting, and team operating practices. Supports the development and adoption of shared AI platforms and services across business and market insights teams.

Leads user experience, interaction, and visual design for data-driven B2B and B2B2C products. Creates prototypes, MVPs, dashboards, web and mobile applications, chatbots, voice interfaces, and digital assistants using human-centered design, Lean UX, and Design Thinking. Collaborates with customers, product managers, technology teams, marketing, and regional stakeholders to conduct research, iterate designs, establish design patterns, and deliver accessible, engaging experiences across multiple form factors.

Designs customer and product experiences for B2B and B2B2C data products, including dashboards, chatbots, web and mobile applications, and voice interfaces. Creates prototypes and MVPs using human-centered design, Lean UX, and Design Thinking. Develops personas, user journeys, wireframes, visual mockups, and interaction patterns while collaborating with product, technology, marketing, regional, and end-user teams.

Leads the design, development, deployment, and evaluation of machine learning solutions for forecasting, recommendation, propensity modeling, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners across functions, presents insights to leadership, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the organization’s technical direction.

Leads the design, development, deployment, and evaluation of machine learning solutions, including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies embeddings and foundation-model techniques, measures business impact, and partners with cross-functional stakeholders. Mentors data scientists and AI engineers, influences technical direction, supports hiring, and communicates technical recommendations to senior leadership.

Leads the design, deployment, and evaluation of machine learning solutions including forecasting, recommendation, propensity, fraud, and customer analytics models. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, and partners with cross-functional stakeholders. Mentors data scientists and AI engineers, influences technical direction, supports hiring, and communicates technical recommendations to senior leadership.

Leads the design, development, deployment, and evaluation of machine learning solutions for forecasting, recommendations, propensity modeling, fraud detection, risk modeling, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners with cross-functional stakeholders, presents technical insights, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and AI technical strategy.

Leads the design, deployment, and evaluation of machine learning solutions, including predictive modeling, forecasting, recommendations, fraud detection, and customer analytics. Defines experimentation frameworks, applies foundation-model embeddings, measures business impact, partners with cross-functional stakeholders, and mentors data scientists and AI engineers. Contributes to hiring and the technical direction of Mastercard’s AI organization.

Leads the design, development, deployment, and evaluation of machine learning solutions, including predictive models, recommendation systems, forecasting, embeddings, and foundation-model applications. Defines experimentation frameworks and success metrics, measures business impact, partners with cross-functional stakeholders, presents technical recommendations, and mentors data scientists and AI engineers. The role also contributes to hiring, capability development, and the organization’s long-term technical direction.