Analyst, Platform Journey Analytics and Measurement for Support

Minimum qualifications:

• Bachelor's degree in Computer Science or equivalent practical experience.
  
• Experience in system design or one or more programming language (e.g., Java, C++, Python, etc.).
• Experience in manipulating data sets with SQL and using statistics to solve technical problems.
• Experience in solution engineering.
• Experience in stakeholder management, professional services, or technical consulting.

Preferred qualifications:

• Experience with website analysis.
• Experience in running experiments.
• Experience in strategic analysis or operations management support.
• Experience in presenting to executives (e.g., consulting, management reporting, Six Sigma certification).
• Experience in SQL and one other language such as Python, Java, or R.

About the job

gTech Ads is responsible for all support and media and technical services for customers big and small across our entire Ad products stack. We help our customers get the most out of our Ad and Publisher products and guide them when they need help. We provide a range of services from enabling better self help and in-product support, to providing better support through interactions, setting up accounts and implementing ad campaigns, and providing media solutions for customers business and marketing needs and providing complex technical and measurement solutions along with consultative support for our large customers. These solutions range from bespoke and customized ones for our customers to scalable support for millions of customers worldwide. Based on the evolving needs of our ads customers, we partner with Sales, Product and Engineering teams within Google to develop better solutions, tools, and services to improve our products and enhance our client experience. As a cross-functional and global team, we ensure our customers get the best return on investment with Google and we remain a trusted partner.

The Data, Architecture, Tools & Analytics (gDATA) team supports the gTech Ads organization. gData manages and utilizes large data sets to solve difficult, non-routine analysis problems while also providing operational analytics and reporting. The team combines investigative excellence, objectivity, and an understanding of business strategies and operations to enable gTech and the Ads ecosystem business to drive smart business decisions.

Google creates products and services that make the world a better place, and gTech’s role is to help bring them to life. Our teams of trusted advisors support customers globally. Our solutions are rooted in our technical skill, product expertise, and a thorough understanding of our customers’ complex needs. Whether the answer is a bespoke solution to solve a unique problem, or a new tool that can scale across Google, everything we do aims to ensure our customers benefit from the full potential of Google products.

To learn more about gTech, check out our video.

The US base salary range for this full-time position is $97,500-$140,000 + 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

• Conduct quantitative data analysis to make product and business recommendations, including impact analysis, market and user understanding, strategic analysis, and user behavior.
• Deliver effective presentations of findings and recommendations to multiple levels of stakeholders.
• Develop, plan, and execute experiments. Build and prototype ideas on the product at scale.
• Collaborate with cross-functional stakeholders to understand their business needs and complete end-to-end analysis that includes data gathering, analysis, ongoing scaled deliverables, and presentations.
• Develop a comprehensive understanding of Google data structures and metrics, advocating for changes where needed for scaled support.