Google's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. Support the development and implementation of data-driven solutions with a focus on large language models (LLMs) and generative AI to solve key business problems. Help optimize support operations, automate case routing, and ultimately make Google Ads products more usable for our customers.
Requirements
- coding (e.g., Python, R, SQL)
- querying databases
- statistical analysis
Responsibilities
- Support the development and implementation of data-driven solutions with a focus on large language models (LLMs) and generative AI to solve key business problems.
- Help optimize support operations, automate case routing, and ultimately make Google Ads products more usable for our customers.
- Collaborate with cross-functional partners to identify challenges and opportunities, translating business needs into actionable data science solutions.
- Contribute to "problem solutioning" and "solution translating," shepherding projects from ideation to implementation and ensuring complex findings are communicated clearly to both technical and non-technical stakeholders.
- Help pioneer the future of gTech by staying ahead of the curve, applying emerging trends in data science to take on the impossible problems that stand between gTech and success.
Other
- 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.
- 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.
- draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations.
- 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.
