Senior Business Data Scientist, Marketing Science, Measurement and Optimization

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.

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.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $163000 - $236000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google.

Responsibilities

• Provide support in media and marketing measurement and optimization that require expertise in advanced analytics work, with special focus on applying data science to marketing analysis approaches.
• Drive advanced analytics work including experimentation, measurement and modeling.
• Identify patterns and behaviors that are effective predictors of performance and critical drivers for a successful media and marketing plan.
• Develop evaluation frameworks for large-scale models, new metrics, and investigate anomalies. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods.

Minimum qualifications:

• Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
  
• 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  
• Experience in causal inference, A/B testing, statistical modeling, or machine learning.

Preferred qualifications:

• 6 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
  
• Experience in campaign brand or conversion lift measurement and using analytical insights to guide media and marketing planning, or working with digital marketing: performance incrementality geo experiments (match market tests).
• Experience delivering analysis, fully automated analytics pipelines or audience segmentation and propensity modeling.
• Understanding of Bayesian approaches and modeling frameworks.
• Ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership with cross-functional stakeholders.

In most instances, this position requires in-person interviews as part of the hiring process.