Business Data Scientist, Ads Marketing Analytics
Google Inc., Kirkland, Washington, United States, 98034
Business Data Scientist, Ads Marketing Analytics
Location: Kirkland, WA, USA
Benefits include:
Health, dental, vision, life, disability insurance
Retirement Benefits: 401(k) with company match
Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
Baby Bonding Leave: 18 weeks
Holidays: 13 paid days per year
About the job Google's leadership team hand‑picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior‑level executives, roll‑up your sleeves to help drive implementation and check back‑in to see the impact of your recommendations.
As a Data Scientist on the Ads Marketing data science team, you will perform data analytics, drive initiatives in experimentation, measurement and advance machine learning modeling capability to support global marketing programs. In collaboration with a multidisciplinary team of marketing, product management, data scientists and engineers, you will tap into the underlying data, develop and align on key metrics/methodologies and generate insights that enable marketers to develop powerful, highly effective marketing programs. You will leverage core Data Science expertise to design, prototype and build out analysis pipelines to support initiatives and Marketing campaigns at scale, perform analytics, design and execute on experimentation, and conduct incrementality measurement analysis to inform on key strategic decisions of the marketing programs across the entire Ads Marketing space, from acquisition, onboarding, and growth.
Salary The US base salary range for this full‑time position is $141,000‑$202,000 + 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.
Responsibilities
Work with large, complex data sets. Solve complex analysis problems, applying advanced investigative methods (such as statistical and machine learning models) as needed. Conduct analysis that includes problem formulation, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of Ads marketing programs.
Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed.
Interact cross‑functionally, making business recommendations (e.g. cost‑benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for business priorities.
Qualifications
Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Preferred qualifications
PhD degree in Statistics or related quantitative discipline.
4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Experience in controlled experiment design and causal inference methods.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents‑to‑be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
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Benefits include:
Health, dental, vision, life, disability insurance
Retirement Benefits: 401(k) with company match
Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
Sick Time: 40 hours/year (statutory, where applicable); 5 days/event (discretionary)
Maternity Leave (Short-Term Disability + Baby Bonding): 28-30 weeks
Baby Bonding Leave: 18 weeks
Holidays: 13 paid days per year
About the job Google's leadership team hand‑picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior‑level executives, roll‑up your sleeves to help drive implementation and check back‑in to see the impact of your recommendations.
As a Data Scientist on the Ads Marketing data science team, you will perform data analytics, drive initiatives in experimentation, measurement and advance machine learning modeling capability to support global marketing programs. In collaboration with a multidisciplinary team of marketing, product management, data scientists and engineers, you will tap into the underlying data, develop and align on key metrics/methodologies and generate insights that enable marketers to develop powerful, highly effective marketing programs. You will leverage core Data Science expertise to design, prototype and build out analysis pipelines to support initiatives and Marketing campaigns at scale, perform analytics, design and execute on experimentation, and conduct incrementality measurement analysis to inform on key strategic decisions of the marketing programs across the entire Ads Marketing space, from acquisition, onboarding, and growth.
Salary The US base salary range for this full‑time position is $141,000‑$202,000 + 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.
Responsibilities
Work with large, complex data sets. Solve complex analysis problems, applying advanced investigative methods (such as statistical and machine learning models) as needed. Conduct analysis that includes problem formulation, data gathering and requirements specification, processing, analysis, ongoing deliverables, and presentations.
Design and analyze controlled experiments or counterfactual causal inference studies to examine the incremental impact of Ads marketing programs.
Build and prototype analysis pipelines iteratively to provide insights at scale. Develop comprehensive knowledge of Google data structures and metrics, advocating for changes where needed.
Interact cross‑functionally, making business recommendations (e.g. cost‑benefit, forecasting, experiment analysis) with effective presentations of findings at multiple levels of stakeholders through visual displays of quantitative information.
Develop and automate reports, iteratively build and prototype dashboards to provide insights at scale, solving for business priorities.
Qualifications
Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Preferred qualifications
PhD degree in Statistics or related quantitative discipline.
4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree.
Experience in controlled experiment design and causal inference methods.
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents‑to‑be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy, Know your rights: workplace discrimination is illegal, Belonging at Google, and How we hire.
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
#J-18808-Ljbffr