Data Science Manager, Marketing

Data Science Manager, Marketing

Find the user. Find the magic. Connect the two. At its core, marketing at Google starts with the user and ends with technology, 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 – break the rules, redefine the medium, make the user the hero, and ultimately let the technology speak for itself.

As a Data Science Manager in the Marketing team, you will lead projects, translating business problems into investigative solutions and you will guide your team to implement data science solutions, improve data, develop metrics, and build models for business insights. You will also foster knowledge sharing and develop your team's talent.

You will also be a Marketing Mix Modeling (MMM) specialist, who will play a strategic and technical role in driving all things media, marketing, 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.

Responsibilities include:

• Provide support in media strategy, measurement, and optimization that requires expertise in advanced analytics work, with special focus on MMMs.
• Partner with internal teams in advanced analytics work including data pipelines, experimentation, measurement, and modeling.
• Identify patterns and behaviors that are effective predictors of performance and critical drivers for a successful media plan.
• Deliver customer-centric, data-driven approach, based on a people-based marketing strategy to build, segment, and test audiences for best business results.
• Develop evaluation frameworks for ML and LLM models, large-scale models, new metrics, and investigate anomalies. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods.