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 have a blend of marketing, statistics and data infrastructure experience. You will support your team by delivering pieces of project work including supporting the implementation of data science solutions, supporting the improvement of data pipelines, running geo-experiments, marketing mix models (MMM), meta analysis or helping your team develop evaluation metrics that provide insights to the business.
You will play a technical role in driving all things media, marketing, analytics, and partnering with internal teams to evaluate 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 issues. Regardless of geographic location, you will maintain a global scope, working with teams operating across regions and marketing entities.
Responsibilities
- Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with a focus on applying data science to marketing and analysis approaches.
- 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.
- 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.
Qualifications
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.
- Experience managing end-to-end brand measurement frameworks, including brand lift studies, marketing mix modeling (MMM), or multi-touch attribution (MTA).
Preferred qualifications:
- 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.
- Experiences with experimental design and supervised/unsupervised machine learning approaches for both regression and classification tasks.
- Experience delivering meta 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.