Minimum qualifications:
- Master's degree in a quantitative discipline such as Statistics, Development, 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.
- PhD in Statistics, Mathematics, Economics, Development or Applied Science 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, or a relevant PhD degree.
- Experience in Computer Vision and NLP in the context of marketing analytics and the ability to bring cutting edge generative AI technologies to customer problems in marketing.
- Experience delivering insights from ML to customers (e.g., problem scoping/definition, modeling, interpretation).
- Experience using or deploying digital analytics and measurement solutions.
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About the job
In this role, you will help measure and optimize marketing ROI for Google's largest clients. You will build bespoke models that address client's key business challenges.
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.
Responsibilities
- Lead data science aspects of client engagements in the area of marketing effectiveness and marketing portfolio management with deep knowledge of ML and statistics.
- Collaborate withcustomers to unpack their problems and identify the best statistical techniques that can solve the problem; own the development of end-to-end modeling framework.
- Engage important stakeholders to assess data and model readiness and be able to scale a proof-of-concept to a larger solution.
- Work with customers and internal teams to translate data and model results into tactical and strategic insights that are actionable for decision-making. Co-present to and work with clients to integrate recommendations into business processes.
- Collaborate with Product or Development teams to increase and optimize capabilities of our Applied DS team, employing methods which create opportunities for scale, proactively helping to drive innovation.