Senior Business Data Scientist Manager, Google Cloud Marketing
Google Inc., Seattle, WA, United States
Senior Business Data Scientist Manager, Google Cloud Marketing
Kirkland, WA; New York, NY; Seattle, WA; Sunnyvale, CA
We highlight our comprehensive benefits package, available to all eligible U.S. based employees. Benefits for this role 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 per year (increased to 69 hours per year for Seattle) including 5 discretionary sick days per instance
Maternity leave (short-term disability + baby bonding): 28-30 weeks
Baby bonding leave: 18 weeks
Holidays: 13 paid days per year
Required Qualifications
Master's degree in a quantitative discipline such as statistics, engineering, sciences, or equivalent practical experience.
9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience managing and developing teams of data scientists.
Experience building and deploying machine learning models for business applications (e.g., lead scoring, attribution, forecasting).
Preferred Qualifications
11 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
6 years of experience as a people manager within a technical leadership role.
Experience with cloud computing platforms (e.g., Google Cloud Platform, BigQuery, Vertex AI) and handling large-scale datasets.
Deep understanding of the B2B enterprise SaaS marketing and sales cycle, demand generation funnels, and marketing technology stacks (e.g., Salesforce, Marketo).
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 insights from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy 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.
The Google Cloud Marketing Data Science and Analytics (DSA) team is responsible for end-to-end development of data assets, data science and machine learning capabilities, and analytics and insights for Google Cloud Marketing. Our mission is to empower Google Cloud's growth by transforming raw data into actionable intelligence. We leverage cutting-edge data science, machine learning, and analytics to decode and predict customer behavior, measure the impact of marketing motions and programs, and optimize every facet of our marketing strategy to accelerate Google Cloud's growth.
As the Head of Data Science for Google Cloud Marketing, you will define and lead the strategic roadmap for data science and machine learning to accelerate our B2B go-to-market (GTM) motions. You will lead a team of data scientists to build the intelligence engine that powers how we identify, engage, and convert customers globally.
US base salary range for this full-time position is $240,000-$334,000 plus bonus, equity, and benefits. 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
Define and execute the long-term vision for data science within Cloud Marketing, building scalable ML/AI capabilities that optimize the B2B customer journey.
Oversee the development and deployment of robust AI-native data science capabilities and predictive models to accelerate marketing motions and personalize marketing outreach at scale. Deploy intelligent agents to automate experiences and drive engagement across various channels.
Lead the creation of sophisticated attribution models and incrementality experiments to quantify marketing impact, optimize media spend, and unlock insights into funnel performance.
Partner with GTM, sales operations, and engineering leadership to integrate data science capabilities into operational workflows (e.g., CRM systems), ensuring high adoption and alignment with business goals.
Build, mentor, and lead a high-performing team of data scientists, fostering a culture of technical excellence, innovation, and thorough statistical methodology.
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, 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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Kirkland, WA; New York, NY; Seattle, WA; Sunnyvale, CA
We highlight our comprehensive benefits package, available to all eligible U.S. based employees. Benefits for this role 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 per year (increased to 69 hours per year for Seattle) including 5 discretionary sick days per instance
Maternity leave (short-term disability + baby bonding): 28-30 weeks
Baby bonding leave: 18 weeks
Holidays: 13 paid days per year
Required Qualifications
Master's degree in a quantitative discipline such as statistics, engineering, sciences, or equivalent practical experience.
9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
Experience managing and developing teams of data scientists.
Experience building and deploying machine learning models for business applications (e.g., lead scoring, attribution, forecasting).
Preferred Qualifications
11 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
6 years of experience as a people manager within a technical leadership role.
Experience with cloud computing platforms (e.g., Google Cloud Platform, BigQuery, Vertex AI) and handling large-scale datasets.
Deep understanding of the B2B enterprise SaaS marketing and sales cycle, demand generation funnels, and marketing technology stacks (e.g., Salesforce, Marketo).
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 insights from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy 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.
The Google Cloud Marketing Data Science and Analytics (DSA) team is responsible for end-to-end development of data assets, data science and machine learning capabilities, and analytics and insights for Google Cloud Marketing. Our mission is to empower Google Cloud's growth by transforming raw data into actionable intelligence. We leverage cutting-edge data science, machine learning, and analytics to decode and predict customer behavior, measure the impact of marketing motions and programs, and optimize every facet of our marketing strategy to accelerate Google Cloud's growth.
As the Head of Data Science for Google Cloud Marketing, you will define and lead the strategic roadmap for data science and machine learning to accelerate our B2B go-to-market (GTM) motions. You will lead a team of data scientists to build the intelligence engine that powers how we identify, engage, and convert customers globally.
US base salary range for this full-time position is $240,000-$334,000 plus bonus, equity, and benefits. 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
Define and execute the long-term vision for data science within Cloud Marketing, building scalable ML/AI capabilities that optimize the B2B customer journey.
Oversee the development and deployment of robust AI-native data science capabilities and predictive models to accelerate marketing motions and personalize marketing outreach at scale. Deploy intelligent agents to automate experiences and drive engagement across various channels.
Lead the creation of sophisticated attribution models and incrementality experiments to quantify marketing impact, optimize media spend, and unlock insights into funnel performance.
Partner with GTM, sales operations, and engineering leadership to integrate data science capabilities into operational workflows (e.g., CRM systems), ensuring high adoption and alignment with business goals.
Build, mentor, and lead a high-performing team of data scientists, fostering a culture of technical excellence, innovation, and thorough statistical methodology.
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, 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