Top Machine Learning Jobs in Dublin

Leads advanced data science and machine learning initiatives to discover healthcare affordability and payment integrity opportunities. Develops anomaly detection, clustering, graph analytics, explainable AI, generative AI, and evidence-generation methods using large-scale healthcare data. Partners with product, engineering, analytics, and domain stakeholders to translate patterns into actionable hypotheses, operationalize analytical assets, and improve model validation. Provides technical leadership, establishes analytical standards, mentors data scientists, and guides ambiguous initiatives from problem definition through delivery.

Provides strategic and technical leadership for a large-scale software engineering organization. Leads enterprise software, cloud-native architecture, AI-powered solutions, engineering standards, DevOps, CI/CD, and responsible AI adoption. Guides multidisciplinary engineering leaders, mentors senior technical staff, evaluates emerging technologies, and partners with product and business stakeholders to deliver scalable healthcare technology solutions.

Develop and enhance actuarial pricing and forecasting solutions for U.S. health insurance using statistical techniques, machine learning, AI, and large healthcare datasets. Responsibilities include dataset development, model validation, data quality assurance, reconciliation, predictive modeling, and collaboration with actuarial, data science, product, and engineering teams. The role also supports continued progress toward actuarial qualification through a structured development program.

Research and develop innovative data science methods for Mastercard’s Test & Learn analytics platform. Apply machine learning, causal inference, and generative or agentic AI to high-volume business problems, translate research into scalable products, collaborate with product and engineering teams, and influence strategic decisions through advanced analytics.

Conduct analytic research for Mastercard’s Test & Learn platform, developing innovative data science methods and scalable solutions for complex business problems. Collaborate with product management, engineering, and business leaders to identify customer needs, guide implementation, and influence commercial decisions using machine learning, causal inference, and generative or agentic AI. Manage cross-functional workstreams, communicate effectively with stakeholders, solve problems, and mentor teammates.

Conduct analytic research for Mastercard’s Test & Learn platform, developing novel data science methods involving machine learning, causal inference, and generative or agentic AI. Collaborate with product management, engineering, and business leaders to translate research into scalable commercial products that solve customer challenges. Influence business decisions using high-volume datasets, manage cross-functional workstreams, communicate findings, and mentor teammates.

Conduct analytic research for Mastercard’s Test & Learn platform, developing machine learning, causal inference, generative AI, and agentic AI solutions for complex business problems. Collaborate with product management, engineering, and business leaders to translate research into scalable products and commercial solutions. Analyze high-volume datasets, influence business decisions, manage cross-functional workstreams, communicate findings, and mentor teammates.

Conduct analytic research for Mastercard’s Test & Learn platform, developing innovative data science methods and scalable solutions for complex business challenges. Collaborate with product management, engineering, and business leaders to identify customer needs, guide implementation, and influence commercial decisions using high-volume datasets. Apply machine learning, causal inference, generative AI, and agentic AI while mentoring teammates and managing cross-functional workstreams.

Conducts analytic research for Mastercard’s Test & Learn platform, developing novel data science methods and scalable solutions. Applies machine learning, causal inference, and generative or agentic AI to high-volume datasets and commercial problems. Collaborates with product management, engineering, and business leaders to guide product implementation, solve customer needs, manage cross-functional workstreams, and mentor teammates.

Leads strategy, roadmap, backlog, delivery, and operational performance for AI-powered products and platform capabilities. Partners with engineering, data science, business, risk, operations, and customer success teams to define requirements, prioritize features, establish AI rules and success metrics, and deliver scalable solutions. Oversees Agile and SAFe ceremonies, release planning, APIs, integrations, data flows, platform architecture, monitoring, experimentation, and continuous optimization.

Leads strategy, roadmap, backlog, delivery, and operationalization of AI-powered products and platform capabilities. Defines AI rules, decision criteria, success metrics, and exception processes while partnering with engineering, data science, business, risk, operations, and customer success teams. Oversees Agile delivery, technical trade-offs, APIs, data flows, scalability, monitoring, and continuous optimization of AI outcomes.

Conduct analytic research for Mastercard’s Test & Learn platform, developing machine learning, causal inference, and generative AI solutions for complex business problems. Collaborate with product management, engineering, and business leaders to translate research into scalable products and commercial solutions. Apply innovative analytics to high-volume datasets, guide implementation, manage cross-functional workstreams, communicate findings, solve problems, and mentor teammates.

Research and develop innovative data science methods for Mastercard’s Test & Learn analytics platform. Apply machine learning, causal inference, and generative or agentic AI to high-volume datasets and commercial challenges. Collaborate with product management, engineering, and business leaders to translate analytical ideas into scalable products, guide implementation, solve customer needs, manage workstreams, and mentor teammates.

Leads strategy, roadmap, backlog, delivery, and operational performance for AI-powered products and platform capabilities. Partners with engineering, data science, business, risk, and operations teams to define requirements, manage AI rules, prioritize features, establish success metrics, and optimize outcomes. Provides technical product leadership across APIs, data flows, cloud platforms, scalability, security, and platform architecture while coordinating agile delivery and communicating priorities, risks, and results to leadership.

Conduct analytic research for Mastercard’s Test & Learn platform, developing novel data science methods and scalable solutions for business experimentation and optimization. Collaborate with product management, engineering, and business leaders to identify customer needs, guide implementation, analyze high-volume datasets, and influence commercial decisions. The role requires machine learning, causal inference, generative or agentic AI experience, strong communication, project management, and mentoring skills.

Research and develop innovative data science functionality for Mastercard’s Test & Learn analytics platform. Apply machine learning, causal inference, and generative or agentic AI to high-volume datasets and commercial problems. Collaborate with product management, engineering, and business leaders to translate analytical concepts into scalable products and solutions. The role also requires strong communication, project management, problem-solving, and mentoring skills.

Conduct analytic research for Mastercard’s Test & Learn platform, developing novel data science methods and scalable solutions for business challenges. Collaborate with product management and engineering to translate analytical ideas into products, influence commercial decisions using high-volume datasets, and identify innovative customer solutions. The role requires expertise in machine learning, causal inference, generative or agentic AI, strong business acumen, cross-functional communication, project management, and mentoring.

Own the vision and roadmap for a foundational agentic AI capability. Define its reasoning, generation, decision models, taxonomy, and knowledge structures; translate ambiguous problems into product requirements; and partner with data science and ML teams on model behavior and inference design. The role requires representing progress to senior stakeholders and shaping AI-first product standards across the organization.

Leads architecture for workforce technology platforms, representing product families in technical governance and shaping target-state architecture. Provides technical direction, evaluates emerging technologies, drives scalable and secure system designs, and influences product functionality and engineering practices. Integrates enterprise-approved AI capabilities into architecture and SDLC workflows with validation, auditability, resiliency, and security controls. Acts as a technical subject matter expert and collaborates with engineering teams, contractors, vendors, and decision-makers.

Leads AI transformation, governance, quality oversight, risk management, and responsible adoption across Pfizer Global Supply and QSEO. Establishes GxP-compliant AI lifecycle practices, inspection-readiness frameworks, governance forums, portfolio monitoring, inventory management, metrics, and reporting. Advises senior leaders on AI regulations, deployment risks, investment priorities, and compliance while leading cross-functional initiatives and influencing stakeholders across Quality, Digital, Operations, and R&D.

Leads hands-on development of AI and agentic systems for Mastercard’s consulting-focused AI platform. Designs scalable services, integrations, workflows, data pipelines, and reusable agent capabilities; integrates LLMs, AI services, orchestration platforms, knowledge bases, and vector search. Provides technical direction, reviews code, mentors engineers, coordinates vendors, supports migrations, and ensures secure, reliable, compliant, production-ready solutions.

Leads enterprise architecture for employee platforms, advising teams on technology selection, developing multi-year roadmaps, and guiding secure, high-quality cloud application development. Applies AI-enabled engineering patterns with human validation, auditability, resiliency, and security controls. Evaluates emerging technologies, represents the organization in technical forums, serves as a subject matter expert, and communicates architecture decisions to senior executives. The role also requires product ownership experience and may involve managing a small team.

Own internal security engineering across endpoint protection, identity and access, email and SaaS security, detection engineering, threat hunting, incident response, forensics, threat intelligence, and security automation. The role requires building and operating controls across Windows and macOS, leading incidents, writing SIEM detections, and applying Python, Go, AI, and machine learning to improve security operations.

Leads a global team of 17–22 data scientists and analytics professionals developing optimization, predictive risk modeling, and Applied AI solutions for pharmaceutical manufacturing. Sets technical direction, builds reusable analytics products, reduces quality and supply disruption risk, improves efficiency and throughput, and partners with senior executives across manufacturing, quality, technology, and supply functions.

Leads BGE’s data science and analytics function, managing teams and delivering diagnostic, predictive, and prescriptive analytics. Responsibilities include strategy, stakeholder engagement, analytical product development, cloud data solutions, model governance, responsible AI, automation, and lifecycle management. The role also requires coaching talent, prioritizing high-value opportunities, ensuring data quality and compliance, and deputizing for the Head of the Data Centre of Excellence.