Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations.
As a Data Scientist on the Ads Marketing data science team, you will perform data analytics, drive initiatives in experimentation and measurement, and advance machine learning capabilities. This includes designing and building innovative AI agents to enhance operational efficiency and unlock significant Operational Expenditure (OpEx) and time savings across global marketing programs. In collaboration with a multidisciplinary team of marketing, product management, data scientists, and engineers, you will tap into underlying data, develop key metrics and methodologies, and generate insights. These insights, often powered by both analysis and custom-built AI agents, will enable marketers to develop powerful, highly effective campaigns. You will leverage core data science expertise to design, prototype, and build analysis pipelines and agentic systems to support initiatives across the entire Ads Marketing lifecycle from acquisition, onboarding and growth while conducting incrementality measurement to inform strategic decisions. You will build investigative frameworks and measurement capabilities to generate data-driven insights that drive business growth. You will effectively present and communicate these insights and investigative results to marketing partners and leadership, informing key decision-making.
Responsibilities
- Design, develop, and implement AI-powered agents and automation solutions to enhance efficiency across marketing and ads marketing analytics.
- Define, measure, and report on the impact of AI agent deployments, quantifying improvements in OpEx and team velocity. Utilize data-driven insights to iterate on and optimize these agents, ensuring continuous value delivery and alignment with goals for marketing efficiency.
- Work with data sets and solve analysis problems, applying advanced investigative methods (such as statistical and machine learning models) as needed. Conduct analysis that includes problem formulation, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
- Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of Ads marketing programs.
Qualifications
Minimum qualifications:
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical 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.
- Ability to communicate in English fluently to communicate with different customers and stakeholders.
Preferred qualifications:
- 6 years of work experience (e.g., statistician, computational biologist, bioinformatician, data scientist, or product analyst), including experience with statistical data analysis such as linear models, multivariate analysis, causal inference, sampling methods.
- Experience with NoSQL development or analytics tools (e.g., object-oriented programming, R, Python, etc.) and data visualization.
- Experience with statistical and quantitative modeling and forecasting.
- Experience with machine learning techniques.
- Excellent investigative skills with the ability to analyze research or performance data and apply that analysis to optimize programming strategy.