Business Data Scientist, Marketing

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 Business Data Scientist in the Marketing team, you will drive key analytical projects that deliver a scaled impact for Google Marketing across media campaigns.

You will partner with cross-functional teams to deliver pieces of project work including supporting the implementation of data science solutions, supporting the automation of data pipelines, running meta-analysis to understand drivers of marketing return on investment and helping your team develop evaluation metrics that provide better signals for the business to optimize towards.

As a Marketing Measurement Specialist you will play a strategic and technical role in driving all things media, data, analytics, and partnering with internal teams to evaluate strategic initiatives. Using first-party and third-party data sources, you will create innovative solutions to demonstrate the effectiveness of Google’s media investment. At Google-scale, this implies working on our industry’s toughest challenges. You will maintain global consistency, while keeping regional focus. This role requires working with teams operating across regions and marketing entities.

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:

• 6 years of experience delivering marketing analytics, marketing mix modeling, geo experiments, meta analysis, audience segmentation and propensity modeling.
• Experience delivering 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.