Business Analyst Lead, Go-To-Market

Key Skills

SQL, Data Modelling, Statistical modeling, Forecasting

Job Description

Minimum qualifications:

• Bachelor's degree in Mathematics, Economics, Engineering, Data Science, a related field, or equivalent practical experience
• 5 years of experience working as an analyst or a related role in a data, consulting, or financial services environment
• Experience making business decisions using quantitative methods and building predictive models
• Experience with SQL

Preferred qualifications:

• Experience with financial modeling
• Experience with cross-functional partnership and stakeholder management
• Experience with data visualization
• Ability to tell a story using data
• Excellent presentation, statistical, quantitative modeling, forecasting, and SQL skills

About the job

The Revenue Acceleration team within the Global Business Organization (GBO) is a global operations team that aligns company priorities with automation and analytics to deliver business growth opportunities to our promoters and customers. We are responsible for the strategy, systems, analytics, and operations of the Recommended Opportunities program. This program drives the growth of Google Ads.

As Business Analyst Lead, you will be part of a highly effective Analytics team. You will work on delivering insights into the performance of Recommended Opportunities and provide recommendations for improving the effectiveness of the program. You will influence program adoption and business growth for the company.

The Go-to-Market Operations (GtM) team ensures Google's complex and ever-evolving Ads business runs smoothly. We are instrumental in setting go-to-market strategy, and ensuring flawless execution and operations against the strategy. We have teams embedded in each of the major Ads business areas as well as global teams that work across the business areas. Team members are analytical and strategic, with a pragmatic sense of how to get things done.

Responsibilities

• Define metrics to evaluate the performance of recommended opportunities and build reporting/dashboards to measure performance.
• Drive insights into program health and effectiveness across products, regions, and markets and effectively communicate key metrics/insights to various partners and stakeholders.
• Drive program improvements through data driven recommendations and partner with cross-functional teams to implement/launch.
• Build data science/machine learning models to predict relevance and outcome of recommendations to improve the overall user experience.
• Develop relationships with internal/external stakeholders and earn trust by telling stories with data.