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.The US base salary range for this full-time position is $163,000-$237,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
Responsibilities
- Provide support in media strategy, measurement and optimization that require expertise in advanced analytics work, with special focus on marketing mix models (MMMs).
- 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 Maths, Economics, Statistics, Engineering, Sciences, 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 working with marketing analytics and media data
Preferred qualifications:
- Experience generating practical solutions for marketing analytics problems and use results to drive business change in partnership with cross-functional stakeholders.
- Experience with Bayesian approaches and modeling frameworks.
- Experience delivering analysis, fully automated analytics pipelines or audience segmentation and propensity modeling.
- Experience with experimental design and supervised/unsupervised machine learning approaches for both regression and classification tasks.
- Experience in root cause analysis to ensure that problems are solved at both a tactical and strategic level.
- Applied knowledge of R or Python for statistical analysis and SQL.