Top Data Science Jobs in Dublin

Leads data science, decision science, and AI strategy across Europe, identifying high-value use cases and scaling analytical products into measurable business outcomes. Establishes standards for experimentation, model governance, responsible AI, deployment, and lifecycle management. Builds and leads a regional data science capability, manages budgets and resources, partners with global and local teams, and ensures solutions reflect diverse European markets, data environments, and business contexts.

Leads Workday’s Content & Tenant Build organization, defining strategy and roadmaps for configuration content creation, storage, orchestration, and migration across customer tenants. Oversees product, engineering, data science, and implementation teams; partners with product, customer experience, field services, and go-to-market organizations; guides platform and API investments; and drives measurable improvements in deployment velocity, adoption, scalability, reliability, security, and cost of ownership.

Leads strategic R&D engagements from presales through delivery, translating scientific and business challenges into AI architectures, product backlogs, MVPs, simulations, integrations, data pipelines, and production solutions. Builds trusted relationships with R&D executives, scientists, engineers, and technical teams; assesses data, compute, feasibility, value, staffing, and delivery plans. Develops reusable architectures and playbooks, oversees technical workstreams, evaluates emerging AI capabilities, and provides feedback to shape Microsoft Discovery products and scalable industry solutions.

Develop GreyNoise’s cybersecurity channel business across Europe by recruiting and activating partners, building joint business plans, enabling partner teams, generating qualified pipeline, and co-selling enterprise and government opportunities. The role manages partner relationships, channel strategy, revenue targets, forecasting, commercial negotiations, partner reviews, technical enablement, demand generation, and cybersecurity event representation.

Own the Mapping & Content product domain end to end, including strategy, prioritization, economics, and outcomes. Lead efforts to match hotel rooms and content across suppliers, languages, and formats with high accuracy and coverage. Partner closely with engineering and data science teams on entity resolution, search, matching, catalog, identity, recommendation, and content-quality problems. Identify high-value failures, make trade-offs between precision and coverage, and help build Nuitee’s product organization in a fast-moving environment.

Manage Independent Data Monitoring Committee and endpoint adjudication projects for clinical trials. Responsibilities include planning schedules and budgets, coordinating innovation, data science, and technology teams, monitoring risks and progress, communicating with stakeholders, and supporting emerging technology integration. The role requires strong project management, organization, communication, and cross-functional collaboration skills, with endpoint adjudication experience preferred.

Support Europe-focused data science, decision science, and AI use cases by preparing and analyzing data, building and evaluating models, applying AI-assisted workflows, and translating findings into business insights. Collaborate with data, product, engineering, governance, and business teams while maintaining responsible AI practices, reproducibility, documentation, and quality standards.

Manage EMEA Security Operations Center analysts supporting 24/7 incident investigation, containment, and response. The role owns regional shift coverage, operational processes, playbooks, quality assurance, analyst training, career development, and service-level performance. It partners with Product, Support, and security teams to improve workflows, automate analyst capabilities, operationalize new services, and track OKRs. The manager also provides technical leadership, stakeholder guidance, and participates in public speaking engagements.

Lead and mentor a data science team developing machine learning systems for threat detection and agentic AI. Set ML technical strategy, standards, roadmaps, and deployment practices; guide projects from research through production; collaborate with security, engineering, and product teams; develop advanced malware and behavioral threat models; communicate insights; and contribute to research, publications, patents, and hands-on technical work.

Leads the design, development, configuration, and maintenance of clinical data systems and study databases. Develops programming solutions for data ingestion, validation, extraction, reporting, analytics, and data review. Translates requirements into compliant, scalable clinical solutions, provides technical leadership and customer expertise, supports validation and quality processes, and mentors junior programmers across clinical trial study teams.

Lead and manage a multidisciplinary software engineering team to design, build, and deliver scalable AI and quantum-infused payment products. Define requirements, drive agile execution, collaborate with data scientists and engineers, research and document solutions, and represent the team externally. Coach talent, enforce performance processes, and champion innovation and AI-assisted development across product lifecycles.

Lead a multidisciplinary engineering team to design, build and scale AI and Quantum-enabled payment solutions. Drive agile delivery, define requirements, productionize Python/Jupyter solutions, deploy on Kubernetes, mentor talent, and engage with internal and external innovation partners.

Lead and manage an agile software engineering team to design, build and scale innovative products that combine Quantum and AI/ML. Define requirements, drive project execution, collaborate with data scientists and engineers, and deploy solutions using Python, Jupyter and containerized virtual environments (including Kubernetes). Coach and grow talent, ensure compliance with standards, and represent the team externally.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

Lead GTM strategy and product positioning for key products, create messaging and content, run campaigns and launches, analyze market and competitive trends, and collaborate cross-functionally to drive adoption, pipeline growth, and customer engagement.

Lead and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

Lead complex data analyses and data science projects using big data technologies. Develop systems, applications, and visual dashboards; assess system usage; improve data quality and processes; and build tools that address security threats and improve network reliability. Communicate technical findings to nontechnical audiences and guide peers through analytical methods, technologies, and system usage.

The Lead Golang Software Engineer develops server solutions, leads technical designs and code reviews, mentors colleagues, and ensures the quality of engineering practices in the Commercial Systems unit.

Data Scientists at QuantCo will analyze data, build machine learning models, and communicate results to stakeholders, aiming for impactful solutions.

As a Data Science Intern, you'll identify frameworks for data-driven business challenges, transform datasets, run analyses, build machine learning models, and communicate results.