Join to apply for the Customer Engagement, Staff Data Scientist, Go-To-Market, Metrics role at Google
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Join to apply for the Customer Engagement, Staff Data Scientist, Go-To-Market, Metrics role at Google
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years work experience with a Master's degree).
- Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 10 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) (or 8 years work experience with a Master's degree).
- Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field.
- 12 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL).
- 5 years of experience developing and managing metrics or evaluating programs/products.
- Experience in running experimentation-based decision-making processes, both quantitatively (inference, stats, etc.) and organizationally (discipline, alignment, stakeholder management).
- Experience in solving unstructured business problems with data science, translating results into impactful business recommendations, and measuring the success of those initiatives.
In this role, you will help serve Google's worldwide user base of more than a billion people. You will provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving team member, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You will make critical recommendations for your fellow Googlers in Engineering, Product Management, and User Experience. You relish analyzing the numbers one minute and communicating your findings to key stakeholders the next to influence product direction and quantify impact.
As a Data Scientist in the Customer Engagement Data Science team, you will help drive the goal of how Google Ads builds customer success through go-to-market (GTM) metrics and measurement of Ads products.
The US base salary range for this full-time position is $183,000-$271,000 + 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
- Align executive cross-functional Ads stakeholders (Sales, Support, Finance, Product) on a cross-organization process and discipline for the quantitative attribution of impact on key product initiatives.
- Provide investigative thought leadership to executive leadership through proactive and strategic contributions, consistently use insights and analytics to drive decisions and alignment throughout the organization.
- Consult with cross-functional stakeholders to improve experimentation velocity and analysis turnaround time through adoption of self-service tools and improved processes.
- Define and report Key Performance Indicators (KPIs) and launch impact as part of regular business reviews with the cross-functional and cross-organizational leadership team. Translate analysis results in business insights or product improvement opportunities. Work with PM, UX, and Engineering to contribute to metric-backed annual and quarterly OKR settings.
Seniority level
Seniority level
Not Applicable
Employment type
Employment type
Full-time
Job function
Job function
General Business, Strategy/Planning, and ConsultingIndustries
Information Services and Technology, Information and Internet
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