#128035728406782662
umen.
About the job
The Business Strategy & Operations organization provides business critical insights using analytics, ensures cross functional alignment of goals and execution, and helps teams drive strategic partnerships and new initiatives forward. We stay focused on aligning the highest-level company priorities with effective day-to-day operations, and help evolve early stage ideas into future-growth initiatives.
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.
The US base salary range for this full-time position is $111,000-$163,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.
Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google .
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.