Performance Lead, YouTube Support Operations
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Minimum qualifications:
- Bachelor's degree in Engineering, Math, Quantitative Science, or related technical field, or equivalent practical experience.
- 1 year of experience working in data analytics, consulting, data science, engineering, or a technical operations role.
- 1 year of experience in statistical problem-solving and analyzing data sets using SQL or comparable coding language (e.g., Python, R, Java, C++).
Preferred qualifications:
- Experience converting data into insights and enabling the team to deploy learnings.
- Experience creating executive communications (e.g., memos, slide decks, etc.) and presenting to non-technical audiences.
About the job
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.
As an Associate in Business Operations and Strategy, you are the ultimate data expert solving highly analytical problems, conducting interviews and synthesizing ideas. You will work with a small team on projects commissioned by Google's executive team, managing your own workstream(s) as you go.
As a Performance Lead within the Performance Analytics and Operations team, you will play a crucial role in leveraging data to understand and improve the effectiveness of YouTube's scaled support systems. You will be responsible for translating complex data into insights that drive decision-making and enhance the user support experience across all YouTube products.
Responsibilities
- Collect, analyze, and interpret complex product, support, and business operations data to identify trends, patterns, and areas for improvement, and to monitor A/B testing and experiments.
- Define, track, and report on key performance indicators (KPIs) related to support channel effectiveness, user behavior, and support system performance, and communicate these insights.
- Identify opportunities to optimize support processes and recommend data-driven solutions with an understanding of underlying systems and technical constraints.
- Partner with product managers, engineers, and support teams to ensure data-driven decisions are integrated into product development and support operations, and communicate technical information to non-technical audiences.
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