Business and Marketing Data Scientist II

Requirements:

• 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).

Nice to Haves:

• 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.

What You'll Be Doing:

• 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.

Perks and Benefits:

• Google's leadership team hand-picks thorny business challenges for members to work on.
• The opportunity to fully immerse yourself in data collection, draw insight from analysis, and develop compelling recommendations.
• Work in small teams to find solutions, communicate recommendations to senior-level executives, and help drive implementation.