Business Data Scientist, Ads and Commerce Finance, YouTube

About the role

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.

Responsibilities

• Own core demand related analysis and reporting cadences, deep-diving into trends to understand drivers of YouTube revenue and identify opportunities for growth.
• Partner closely with Product to understand launches that meaningfully change how we serve ads.
• Provide analytical support and make progress to drive impact to Product strategy, even in ambiguous environments.
• Construct executive level presentations and present complex analytical findings in a clear, concise, and decision-impacting manner.
• Develop and maintain scalable financial tools and infrastructure, including advanced datasets, intuitive dashboards, and robust financial models, to deliver meaningful and timely updates on growth areas and business performance.

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.

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.
• 4 years of experience involving quantitative data analysis related to online advertising.

Qualifications

• Minimum qualifications: Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
• 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.

Skills

• Experience with and passion for using data to solve complex business questions and drive recommendations in a fast-moving environment.
• Experience with writing code to mine insights out of Google’s internal ads logs.
• Experience analyzing external data to understand the motivations and decision-making process of Google’s users and advertisers.
• Ability to communicate findings to executives effectively.

Benefits

• Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
• US: $138000 - $198000 (USD) + 15% bonus target + equity + benefits