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Business Data Scientist, gTech Ads - Job Opportunity at Google

Dublin, Ireland
Full-time
Mid-level
Posted: July 23, 2025
On-site
€85,000 - €120,000 annually based on Dublin market rates for mid-level data science roles at major technology companies, with Google typically offering compensation in the upper quartile of market ranges plus significant equity and bonus components

Benefits

Equal opportunity workplace commitment providing comprehensive protection against discrimination based on race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or veteran status
Disability accommodation support through dedicated Accommodations for Applicants program ensuring inclusive hiring processes
Access to Google's innovative technology stack and cutting-edge AI/ML platforms providing unparalleled professional development opportunities
Global cross-functional collaboration exposure working with Sales, Product, and Engineering teams across multiple time zones
Direct client engagement with Google's largest enterprise customers offering high-visibility project experience

Key Responsibilities

Drive strategic data science initiatives for marketing effectiveness measurement and portfolio optimization for Google's highest-value enterprise clients, directly impacting multi-million dollar advertising investments
Lead collaborative customer discovery sessions to identify complex business challenges and architect comprehensive statistical modeling frameworks that address core business objectives
Execute stakeholder management across technical and business leadership levels to evaluate data infrastructure readiness and scale proof-of-concept solutions into enterprise-grade implementations
Transform complex analytical findings into executive-level strategic recommendations and co-present actionable insights to C-suite decision makers for business process integration
Drive product innovation and capability enhancement through strategic collaboration with Product and Engineering teams, developing scalable methodologies that advance the entire Applied Data Science organization

Requirements

Education

Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, 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 relevant PhD degree

Required Skills

Analytics to solve product or business problems Coding (e.g., Python, R, SQL) Querying databases or statistical analysis Delivering insights from ML to customers (problem scoping/definition, modeling, interpretation) Using or deploying digital analytics and measurement solutions Computer Vision and Natural Language Processing (NLP) in the context of marketing analytics Statistical algorithms typically used in Marketing Analytics Generative AI technologies applied to customer issues in marketing
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Sauge AI Market Intelligence

Industry Trends

Marketing technology is experiencing unprecedented growth with the integration of generative AI and advanced machine learning capabilities, creating massive demand for data scientists who can bridge technical expertise with marketing strategy execution. The shift toward privacy-first advertising ecosystems, driven by iOS 14.5+ changes and cookie deprecation, is creating critical need for sophisticated measurement and attribution modeling expertise that can operate within constrained data environments. Enterprise organizations are increasingly investing in marketing mix modeling and incrementality testing as traditional digital attribution becomes less reliable, driving demand for statisticians with deep understanding of causal inference methodologies. The convergence of computer vision and natural language processing in marketing applications is creating new opportunities for data scientists to develop innovative customer understanding and creative optimization solutions.

Role Significance

Likely part of a 15-25 person Applied Data Science team within the broader gTech Ads organization, with matrix reporting relationships across Product, Engineering, and Sales functions
Mid-to-senior level individual contributor role with significant client-facing responsibilities and strategic influence on product development, positioned as a technical expert and trusted advisor to enterprise customers

Key Projects

Multi-touch attribution modeling for enterprise clients with complex customer journeys spanning multiple channels and touchpoints Marketing mix modeling implementations that quantify the incremental impact of various media investments across traditional and digital channels Incrementality testing frameworks using geo-experiments and synthetic control methodologies to measure true advertising effectiveness Custom measurement solutions for privacy-compliant marketing analytics in cookieless environments

Success Factors

Deep technical expertise in causal inference and experimental design methodologies, as marketing measurement increasingly requires sophisticated statistical approaches to separate correlation from causation in complex media environments Exceptional client communication skills with the ability to translate complex statistical concepts into actionable business insights for senior marketing executives who may not have technical backgrounds Strategic thinking capability to understand broader business context and marketing objectives, enabling the development of measurement frameworks that align with actual decision-making needs rather than purely technical optimization Collaborative leadership skills to work effectively across Product, Engineering, and Sales teams while maintaining technical credibility and driving consensus on complex analytical approaches

Market Demand

Extremely high demand driven by the critical intersection of advanced analytics, marketing technology evolution, and Google's market-leading position in the advertising technology ecosystem

Important Skills

Critical Skills

Statistical modeling and causal inference expertise is absolutely essential as marketing measurement moves beyond simple attribution to sophisticated incrementality testing and marketing mix modeling approaches that require deep understanding of experimental design and econometric methods Python/R programming proficiency combined with SQL database querying skills forms the technical foundation for all analytical work, with increasing importance placed on ability to work with large-scale distributed computing environments and cloud-based data platforms Machine learning implementation experience, particularly in marketing contexts, is critical as automated bidding, audience optimization, and creative personalization become increasingly sophisticated and require data scientists who understand both technical methodology and marketing application

Unique Aspects

Direct access to Google's proprietary advertising data and machine learning infrastructure, providing unparalleled opportunities to work with industry-leading datasets and analytical capabilities
Client portfolio includes the world's largest advertisers across diverse industries, offering exposure to sophisticated marketing challenges and the opportunity to influence billion-dollar media investment decisions
Integration with Google's broader AI and machine learning research initiatives, including potential collaboration with DeepMind and Google Research teams on applied marketing analytics challenges
Opportunity to shape the future of marketing measurement through direct involvement in product development and methodology innovation that will influence industry standards

Career Growth

2-4 years to senior individual contributor roles, 4-6 years to management positions with strong performance and continued skill development in emerging technologies

Potential Next Roles

Senior Data Science Manager leading applied analytics teams Principal Data Scientist focusing on advanced methodology development Marketing Analytics Director at enterprise technology companies Head of Measurement at digital marketing agencies or consultancies

Company Overview

Google

Google maintains the dominant position in global digital advertising with approximately 28% market share and the most comprehensive advertising technology stack including Search, YouTube, Display, and emerging Connected TV offerings.

Undisputed market leader in search advertising and among the top three players in display and video advertising, with unparalleled data assets and machine learning capabilities that create significant competitive advantages
Dublin serves as Google's EMEA headquarters with over 8,000 employees, functioning as a critical hub for international business operations, regulatory compliance, and technical innovation serving European, Middle Eastern, and African markets
Data-driven decision making culture with emphasis on experimentation, technical excellence, and large-scale impact, offering exposure to cutting-edge technology development and collaboration with world-class engineering and product teams
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