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Karkidi

Business Data Scientist, Ads Product Finance, YouTube

Karkidi, Mountain View, California, us, 94039


Minimum qualifications:

Scroll down to find an indepth overview of this job, and what is expected of candidates Make an application by clicking on the Apply button.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.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.Excellent problem solving and technical abilities to drive forecasting, data analysis, and insights for executive audiences (e.g., SQL, R, Python, dashboard creation, advanced financial modeling, statistics), with attention to detail.Experience involving quantitative data analysis related to online advertising and emerging businesses like Shopping, etc.Ability to take initiatives, work in an unstructured environment, and comfortable dealing with ambiguity.About the job:The YouTube Ads Product Finance team partners with YouTube Ads Leadership across Product, Engineering, and Sales (GBO) to drive ads decisions with financial stewardship. We are strategic partners, driving impact through analysis grounded in hard data. We bring a unique point of view and bias to action on a collaborative approach, all while focusing on the development of our people.In this role, you will be a quantitative analyst on the YouTube Ads Finance team. You will have the opportunity to lead core reporting and analytics cadences for YouTube Ads, specifically within emerging products and experiences.Responsibilities:Own core business analysis and reporting cadences, in-depth search into trends to understand drivers and identify opportunities for growth.Provide support and make progress to drive impact to Product strategy, even in ambiguous environments.Demonstrate bias towards action by proactively analyzing data to unlock actionable insights.Construct executive level presentations and present complex findings in a clear, concise, and decision-impacting manner. Build excellent problem solving frameworks and tools to measure key results.

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