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 Data Science Manager in the Marketing Media Lab 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 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 and the industry’s toughest issues, at a global scale.
Minimum qualifications:
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
- 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Preferred qualifications:
- 2 years of experience managing an Analytics or Data Science team, including prioritisation, roadmapping, coaching and performance management.
- Experiences with experimental design and supervised/unsupervised ML approaches for regression and classification tasks.
- Experience of root cause analysis to ensure that problems are solved at both a tactical and strategic level.
- Experience delivering marketing analytics e.g., Marketing Mix Modeling , geo experiments, meta-analysis, audience segmentation and propensity modeling .
- Understanding of Bayesian approaches and modeling frameworks.
- Proven ability to generate practical solutions for marketing analytics problems and use results to drive business change in partnership with cross functional stakeholders.
Responsibilities:
- Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with special focus on marketing analytics methods and data science.
- Partner with internal teams in 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 plan.
- Deliver customer-centric, data-driven approach, based on a people-based marketing strategy to build, segment, and test audiences for best business results.
- Partner with internal teams to scope, build and deliver strategic initiatives driving all things marketing data, with a strong focus on digital marketing data pipelines.
- Lead and develop the team, taking ownership of team roadmapping, initiative prioritization, individual coaching, and ongoing performance management.
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