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Data Scientist, Infrastructure, Marketing - Job Opportunity at Google

Dublin, Ireland
Full-time
Mid-level
Posted: July 19, 2025
On-site
EUR 85,000 - EUR 120,000 annually, which translates to approximately USD 92,000 - USD 130,000. This estimate reflects Google's premium compensation structure, Dublin's competitive tech market, and the specialized nature of combining infrastructure, AI, and marketing analytics expertise.

Benefits

Equal opportunity workplace with comprehensive diversity and inclusion initiatives that foster innovation through varied perspectives
Affirmative action employment practices ensuring fair representation and career advancement opportunities
Accommodation support for employees with disabilities or special needs, demonstrating commitment to inclusive workplace culture
Global career exposure with direct support for international marketing projects across all regions
Access to cutting-edge Google Cloud Platform technologies including Vertex AI and advanced analytics tools

Key Responsibilities

Design and implement comprehensive evaluation frameworks for large-scale machine learning models and LLMs, directly impacting Google's AI product quality and performance metrics across global markets
Architect and maintain enterprise-level data infrastructure including pipelines, dashboards, and business scorecards that transform complex multi-source data into actionable insights for strategic decision-making
Establish robust quality assurance processes and validation protocols that ensure data integrity and reliability for critical internal systems and stakeholder deliverables
Lead cross-functional collaboration with global stakeholders to integrate feedback and requirements into scalable technical solutions that drive measurable business outcomes
Drive end-to-end program management for high-impact analytics, reporting, and optimization initiatives that directly influence Google's marketing strategy and performance optimization

Requirements

Education

Master's degree in Science, Technology, Engineering, or Mathematics or a related field or equivalent practical experience

Experience

3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a PhD degree

Required Skills

Analytics to solve product or business problems Coding (e.g., Python, R, SQL) Querying databases or statistical analysis Cloud Analytics products like GCP (Vertex AI) Business analytics in building big data pipelines, schemas and data sets, within a media data context Reporting tools (e.g., Tableau, Looker, Power BI) Marketing data experience Root cause analysis
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Sauge AI Market Intelligence

Industry Trends

The integration of AI and machine learning in marketing analytics is accelerating rapidly, with companies investing heavily in automated decision-making systems and real-time optimization platforms. This trend is driving unprecedented demand for data scientists who can bridge the gap between technical AI capabilities and practical marketing applications. Cloud-native data infrastructure is becoming the standard for enterprise marketing operations, with Google Cloud Platform, AWS, and Azure competing intensively for market share. Organizations are migrating from on-premise solutions to cloud-based analytics platforms that offer scalability, real-time processing, and integrated AI services. Large Language Models and generative AI are revolutionizing marketing data analysis, enabling more sophisticated customer segmentation, content optimization, and predictive analytics. Companies are racing to implement LLM-powered solutions for marketing automation and customer experience personalization. Privacy regulations like GDPR and evolving cookie policies are forcing a fundamental shift in marketing data collection and analysis methodologies. This regulatory landscape is creating demand for data scientists who understand both technical implementation and compliance requirements.

Role Significance

Typically works within a data science team of 8-15 professionals, collaborating with cross-functional teams including marketing, product management, engineering, and business intelligence. The global liaison aspect suggests coordination with 20-30 professionals across different regions.
This is a mid-to-senior level individual contributor role with significant technical leadership responsibilities. The position requires autonomous decision-making on complex technical problems and direct stakeholder management across global teams, indicating substantial influence on strategic initiatives.

Key Projects

Implementation of real-time marketing attribution models using machine learning algorithms Development of automated anomaly detection systems for marketing campaign performance Creation of unified data platforms integrating multiple marketing channels and customer touchpoints Design of predictive analytics models for customer lifetime value and acquisition optimization Building compliance-ready data governance frameworks for international marketing operations

Success Factors

Technical versatility across the full data science stack, from infrastructure management to advanced statistical modeling, enabling end-to-end project ownership and delivery in complex enterprise environments. Strong business acumen combined with technical expertise, allowing for translation of abstract business requirements into concrete technical solutions that drive measurable marketing performance improvements. Global mindset and cultural adaptability, essential for managing stakeholder relationships across different time zones, regulatory environments, and business practices while maintaining consistent technical standards. Proactive problem-solving approach with strong root cause analysis capabilities, crucial for managing the complexity and scale of Google's marketing data infrastructure and ensuring system reliability. Communication and stakeholder management skills that enable effective collaboration with both technical teams and business leaders, facilitating alignment on technical priorities and project deliverables.

Market Demand

Exceptionally high demand driven by the convergence of AI advancement, marketing technology evolution, and regulatory compliance needs. The specific combination of skills required for this role creates a supply shortage in the market.

Important Skills

Critical Skills

Python programming proficiency is absolutely essential as it serves as the primary language for data manipulation, statistical analysis, and machine learning model development in Google's technical stack. Advanced Python skills enable efficient handling of large-scale datasets and integration with Google's internal tools and platforms. SQL expertise is fundamental for database querying and data extraction from Google's complex data warehouse systems. Mastery of SQL enables efficient data retrieval, transformation, and analysis across multiple data sources and schema designs. Machine learning and statistical analysis capabilities are core to developing predictive models, conducting A/B testing, and generating actionable insights from marketing data. These skills directly impact the ability to drive data-driven decision making and optimize marketing performance. Cloud platform experience, particularly with Google Cloud Platform and Vertex AI, is crucial for leveraging Google's native infrastructure and AI capabilities. This knowledge enables efficient model deployment, scalable data processing, and integration with existing Google services.

Beneficial Skills

Experience with visualization tools like Tableau, Looker, or Power BI enhances the ability to communicate complex analytical findings to non-technical stakeholders and create self-service analytics solutions Marketing domain expertise provides valuable context for interpreting data patterns, understanding customer behavior, and designing relevant analytical approaches for marketing optimization Big data technologies and distributed computing knowledge enables handling of Google's massive datasets and development of scalable analytical solutions Project management and stakeholder communication skills facilitate successful delivery of complex initiatives and effective collaboration with global teams across different functions and regions

Unique Aspects

Opportunity to work with Google's proprietary AI and machine learning technologies including Vertex AI, providing access to industry-leading tools and platforms not available in most organizations
Global scope with direct impact on marketing strategies across all international markets, offering exposure to diverse business challenges and regulatory environments
Integration of multiple technical disciplines including infrastructure engineering, statistical analysis, machine learning, and business intelligence within a single role
Access to Google's vast datasets and computational resources, enabling analysis and model development at scales that few organizations can match
Direct influence on product decisions and marketing strategies that affect billions of users worldwide, providing significant career impact and visibility

Career Growth

Progression to senior individual contributor roles typically occurs within 2-3 years, while transition to management positions generally requires 3-5 years of demonstrated leadership and technical excellence in similar environments.

Potential Next Roles

Senior Data Science Manager leading cross-functional analytics teams Principal Data Scientist specializing in marketing technology and AI Data Science Director overseeing global marketing analytics operations Technical Program Manager for large-scale data infrastructure initiatives Head of Marketing Analytics for regional or product-specific divisions

Company Overview

Google

Google stands as the world's dominant search engine and digital advertising platform, with a comprehensive ecosystem of products including cloud computing, mobile operating systems, and enterprise software solutions. The company's data science capabilities are industry-leading, supported by massive computational resources and access to global-scale datasets that provide unparalleled learning opportunities for technical professionals.

Market leader in digital advertising technology with over 90% search market share globally and dominant positions in mobile operating systems, cloud computing, and enterprise productivity software. Google's technical infrastructure and AI research capabilities set industry standards and influence technological development across multiple sectors.
Google's Dublin office serves as the European headquarters for the company's EMEA operations, housing critical business functions including sales, marketing, data analytics, and regulatory compliance. This location provides strategic access to European markets while offering exposure to global-scale projects and cross-regional collaboration opportunities.
Known for fostering innovation through data-driven decision making, technical excellence, and collaborative problem-solving. The company culture emphasizes continuous learning, experimentation, and the application of cutting-edge technology to solve complex business challenges at unprecedented scale.
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