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.
Global Business Strategy and Operations (GBS&O) is part of the Go-to-Market organization making sure Google's business pursues the strategy and executes. GBS&O architects the future of Google’s global ads business, consisting of pragmatic and investigative and experts in business operations. We build creative ML and Data Science solutions to drive strategy and business impact. We help our organization make tough, smart, and difficult decisions to ensure the Ads Business continues to thrive.
In this role, you will oversee advanced data science and causal inference initiatives that influence core business strategies. Your team will solve business problems across channel architecture optimization, global business organization (GBO) ads policy analytics (identifying business growth and policy enforcement opportunities), and CustomerGeist customer sentiment analytics. By partnering closely with global sales leadership, finance, and strategy teams, you will build econometric models and causal inference frameworks that unlock scalable commercial insights and fundamentally elevate GBO's analytical excellence.
You will design and lead analyses and build data infrastructure that drive major decisions across GBO. You will develop your team into a global center of excellence that elevates GBO's excellence, translating data foundation and insights into transformative commercial strategy.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $192000 - $279000 (USD) + 20% bonus target + bonus + equity + benefits
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benefits at Google.
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.
- 3 years of people management experience building, mentoring, and scaling technical teams of data scientists or engineers.
- Experience in SQL, and Python.
Preferred qualifications:
- 9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
- 8 years of experience in data science, advanced analytics, or business intelligence within enterprise or tech environments.
- 4 years of experience as a people manager within a technical leadership role.
- Proficiency in SQL, Python/R, data warehouse architecture (e.g., BigQuery), and data transformation pipelines.
- Track record developing predictive propensity models and causal inference frameworks (A/B testing, incrementality).
- Excellent communication and stakeholder management skills, with demonstrated success partnering with executive leadership teams.