Minimum qualifications:- Bachelor's degree or equivalent practical experience.
- 7 years of experience analyzing data and generating business insights.
- 7 years of experience developing operational process solutions, and working with cross-functional teams to drive these changes.
- 7 years of experience in a customer or client-facing role supporting service-to-sale or business-to-consumer industries.
Preferred qualifications:- MBA or Master's degree in a related field or CSCMP certification.
- 7 years of experience using data analysis to drive decision making.
- 7 years of experience building relationships with stakeholders or clients.
- Experience in data center equipment environments or computer component manufacturing.
- Knowledge of SQL, analytics and Operations Six Sigma certification or other relevant operations coursework.
- Excellent problem-solving skills with the ability to apply structured thinking and logic to your work and provide solutions to challenges.
About the jobThe US base salary range for this full-time position is $136,000-$197,000 bonus equity benefits. Our salary ranges are determined by role, level, and location. 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- Optimize the consumer support ecosystem by balancing unit cost efficiency with CSAT through an AI-first framework and predictive automation.
- Transform the support organization into a growth catalyst by empowering vendors to drive subscription adoption, expansion, and customer lifetime value.
- Translate support data into product improvements to resolve systemic friction at the source.
- Lead the vendor lifecycle, from negotiation and governance to the onboarding of tech-forward partners for global, agile scalability.
- Establish data-driven governance and real-time feedback loops to ensure global operational excellence and maintain a competitive advantage through AI trends.
