Business Data Scientist, Global Ads, Marketing, Data Solutions

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.

Preferred qualifications:

• Experience in Performance Marketing.
  
• Experience and comfort with engineering best practices, including developing BRDs/PRDs/Design Docs, code reviews, etc., ensuring analytical excellence.
• Proven ability to translate ambiguous business needs into clear technical requirements for impactful data products.
  
• Excellent presentation skills, able to convey complex technical solutions and analysis to senior stakeholders.
  
• Excellent project management skills, adept at managing multiple projects concurrently under tight deadlines in a fast-paced environment.
• Exceptional problem-solving skills, adept at synthesizing data into actionable insights and communicating them effectively.
  

As a Quantitative Analyst, you will be responsible for analyzing large data sets and building expert systems that improve our understanding of the Web and improve the performance of our products. This effort includes performing complex statistical analysis on non-routine problems and working with engineers to embed models into production systems. You will manage fast changing business priorities and interface with product managers and engineers.

Data Scientists within the Marketing Technology and Operations team leverage data to drive strategic decision-making and optimize business processes for ads marketing teams. They are responsible for building data pipelines, developing machine learning models for personalization, and creating solutions to deliver personalized marketing content. This involves analyzing large datasets to understand user behavior, campaign performance, and product adoption trends. By employing advanced statistical techniques and machine learning algorithms, Data Scientists uncover insights that improve the efficiency and effectiveness of marketing efforts, ultimately helping advertisers achieve better results.

Know the user. Know the magic. Connect the two. At its core, marketing at Google starts with technology and ends with the user, bringing both together in unconventional ways. Our job is to demonstrate how Google's products solve the world's problems--from the everyday to the epic, from the mundane to the monumental. And we approach marketing in a way that only Google can--changing the game, redefining the medium, making the user the priority, and ultimately, letting the technology speak for itself.

The US base salary range for this full-time position is $127,000-$187,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.

• Designing and implementing robust data pipelines to collect, process, and transform data from various sources.
• Developing and deploying machine learning models for user segmentation, behavior prediction and content recommendation.
• Collaborating with cross-functional teams to integrate personalized experiences into marketing surfaces.
• Analyzing the impact of personalization efforts and iterating on models and strategies.
• Clearly communicate findings through compelling presentations and visualizations, enabling stakeholders to make informed decisions about website improvements and marketing strategies.