Data Science Research Lead, Ads Insights and Measurement
Google · Bengaluru, Karnataka, India
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- On site
- Full-time
- $180,000 / year
- Bengaluru, Karnataka, India
Job highlights
- Lead Ads Insights and Measurement research at Google.
- Apply causal inference and privacy methods.
- Drive large-scale projects across Google products.
- Define future digital advertising measurement standards.
- Empower a team and shape the industry.
About the role
About the Job
As a Technical Lead on Google’s Advertising Measurement team, you will apply scientific aptitude, excellence, precision, accuracy, expertise, thoroughness and statistical expertise to navigate the complex challenges of a global, privacy-preserving advertising ecosystem. Google is a pioneer in sustaining an open internet through a mutually-reinforcing cycle of ad-planning, optimization, and measurement; in this strategic leadership role, you will be the recognized authority driving that cycle forward.
You will develop, organize, and launch large-scale projects spanning engineering and analysis across Search, Display, YouTube, and beyond. By translating advanced science specifically causal inference and quantitative methodologies into deployed products, you will lead the charge in defining paradigm-shifting measurement standards for the future of digital advertising. Working cross-functionally with Engineers, Product Managers, and Sales, you will adjust global strategies based on your findings, ensuring advertising remains useful for users and results-driven for publishers. We are seeking quantitatively trained experts with a passion for business strategy and a deep appreciation for consumer behavior.
In this role, you won’t just improve products; you will empower an exceptional team to shape the marketing-technology industry globally. If you thrive in fluid, science-driven environments and are ready to leverage data and technology to solve modern advertising’s greatest challenges, your leadership will be the catalyst for the next era of innovation.
Responsibilities
- Apply causal inference and differential privacy methods to design experiments, assess attribution, and develop privacy-preserving marketing products.
- Execute end-to-end analyses including data gathering, EDA, and model development to deliver strategic insights to executives.
- Build iterative analysis pipelines and prototype data structures to provide scalable insights across Google’s complex data ecosystems.
- Collaborate with Product and Engineering team to define and answer quantitative questions regarding incrementality, user behavior, and bidding optimization.
- Provide technical guidance and prioritization for the team, conduct cost-benefit analyses to drive high-level business decisions and product strategy.
Key skills/competency
- Data Science
- Research
- Causal Inference
- Statistical Analysis
- Machine Learning
- Leadership
- Experiment Design
- Data Analysis
- Python
- SQL
Skills & topics
- Data Science
- Research Lead
- Ads Insights
- Measurement
- Causal Inference
- Statistical Analysis
- Machine Learning
- Python
- SQL
- Quantitative Analysis
- Experiment Design
- Data Modeling
- Leadership
- Technical Strategy
How to get hired
- Tailor your resume: Highlight your Master's or PhD in a quantitative field, 8+ years of analytics experience, and expertise in causal inference and statistical software like Python or R.
- Showcase leadership: Emphasize any people management experience and your ability to set and drive technical strategy.
- Quantify achievements: Provide specific examples of how your data analysis and modeling solved product or business problems.
- Prepare for technical interviews: Be ready to discuss statistical concepts, ML on large datasets, and your experience with causal inference methods.
- Understand Google's mission: Articulate your passion for shaping the marketing-technology industry and advancing privacy-preserving advertising.
Technical preparation
Behavioral questions
Frequently asked questions
- What specific quantitative fields are considered for the Data Science Research Lead role at Google?
- Google values a broad range of quantitative backgrounds for this Data Science Research Lead position. This includes degrees in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or any closely related quantitative field. Equivalent practical experience is also highly regarded.
- How much work experience is required for the Data Science Research Lead role at Google?
- For the Data Science Research Lead role, Google requires a minimum of 8 years of work experience. This experience should involve using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases, or statistical analysis. Alternatively, candidates with a PhD can qualify with 6 years of relevant work experience.
- What statistical data analysis techniques are important for this Google role?
- The Data Science Research Lead role emphasizes experience with statistical data analysis such as linear models, multivariate analysis, causal inference, and sampling methods. A deeper understanding of potential outcomes framework and advanced causal inference methods like split-testing, instrumental variables, and difference-in-difference is preferred.
- What are the preferred qualifications for a Data Science Research Lead at Google?
- Preferred qualifications for a Data Science Research Lead at Google include a PhD in a quantitative field, 10 years of experience in statistical data analysis, and 5 years of leadership or people management experience. Expertise in Machine Learning on large datasets and a strong grasp of causal inference methods are also highly valued.
- What kind of projects will a Data Science Research Lead at Google work on?
- A Data Science Research Lead at Google will develop, organize, and launch large-scale projects across engineering and analysis for Search, Display, and YouTube. These projects involve translating advanced science, particularly causal inference and quantitative methodologies, into deployed products that define measurement standards for digital advertising.
- What is the role of a Data Science Research Lead in Google's advertising ecosystem?
- As a Technical Lead on Google’s Advertising Measurement team, the Data Science Research Lead navigates a global, privacy-preserving advertising ecosystem. They are recognized authorities driving a cycle of ad-planning, optimization, and measurement to ensure advertising remains useful for users and results-driven for publishers.