Google
Data Scientist, Customer Experience Lab, Go-To-Market
Google, Washington, District of Columbia, us, 20022
This role may also be located in our Playa Vista, CA campus.Note: By applying to this position you will have an opportunity to share your preferred working location from the following:
Mountain View, CA, USA; Atlanta, GA, USA; Chicago, IL, USA; New York, NY, USA; Los Angeles, CA, USA; San Francisco, CA, USA; Washington D.C., DC, USA .Minimum qualifications:
Master's degree in quantitative disciplines (e.g., Statistics, Operations Research, Bioinformatics, etc.) or equivalent practical experience6 years of experience in a data scientist role and with statistical data analysis (such as linear models, multivariate analysis, stochastic models, sampling methods)Experience with statistical software (e.g., R, SAS, Python), databases, and scripting languages (e.g. SQL)Preferred qualifications:
Experience applying data science methodology to survey research, and with sampling and weightingExperience utilizing Data Engineering for pipelining, scripting, Python coding/querying, and data cleaning for downstream data analysisDomain knowledge in the digital advertising space and familiarity with Google Ads productsDemonstrated leadership in building data science models from start to finish, including defining a problem statement, exploring approaches, conducting analyses, and presenting to stakeholdersAbout The Job
The Business Strategy & Operations organization provides business critical insights using analytics, ensures cross functional alignment of goals and execution, and helps teams drive strategic partnerships and new initiatives forward. We stay focused on aligning the highest-level company priorities with effective day-to-day operations, and help evolve early stage ideas into future-growth initiatives.As part of the Customer Lab team, you will be leading data science analytics among Google’s advertising ecosystem partnering with customer Lab researchers and cross-functional senior leaders across Google’s Support, Product, Engineering, Brand, and business organizations to bring actionable insights to the business. You will develop an understanding of business objectives, risks, challenges, and opportunities to ensure that analytics efforts are supportive of business decision making and are actionable by executive leadership.The Go-To-Market Operations (GtM) team ensures Google's complex and ever-evolving Ads business runs smoothly. We are instrumental in setting go-to-market strategy, and ensuring flawless execution and operations against the strategy. We have teams embedded in each of the major Ads business areas as well as global teams that work across the business areas. Team members are analytical and strategic, with a pragmatic sense of how to get things done.The US base salary range for this full-time position is $146,000-$220,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. 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
Leverage critical thinking and problem statement definition, and decomposition to deliver impactful and actionable outcomes. Communicate and visualize insights to multiple levels of stakeholders with clarity, informing decision-making.Develop data engineering methodologies including data source and feature identification and integration, data pipelining, feature engineering, data wrangling, and analysis using script/code driven methods that can translate from research to production.Analyze and develop explanatory, predictive, and prescriptive models using appropriate mathematical methods including frequentist statistics, Bayesian statistics, time-series analysis, supervised and unsupervised machine learning methods, Natural Language Process (NLP), and semantic analysis.Develop and conduct experiments to validate findings from observational research.Ensure actionability of insights through internal and cross-functional collaboration.Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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Mountain View, CA, USA; Atlanta, GA, USA; Chicago, IL, USA; New York, NY, USA; Los Angeles, CA, USA; San Francisco, CA, USA; Washington D.C., DC, USA .Minimum qualifications:
Master's degree in quantitative disciplines (e.g., Statistics, Operations Research, Bioinformatics, etc.) or equivalent practical experience6 years of experience in a data scientist role and with statistical data analysis (such as linear models, multivariate analysis, stochastic models, sampling methods)Experience with statistical software (e.g., R, SAS, Python), databases, and scripting languages (e.g. SQL)Preferred qualifications:
Experience applying data science methodology to survey research, and with sampling and weightingExperience utilizing Data Engineering for pipelining, scripting, Python coding/querying, and data cleaning for downstream data analysisDomain knowledge in the digital advertising space and familiarity with Google Ads productsDemonstrated leadership in building data science models from start to finish, including defining a problem statement, exploring approaches, conducting analyses, and presenting to stakeholdersAbout The Job
The Business Strategy & Operations organization provides business critical insights using analytics, ensures cross functional alignment of goals and execution, and helps teams drive strategic partnerships and new initiatives forward. We stay focused on aligning the highest-level company priorities with effective day-to-day operations, and help evolve early stage ideas into future-growth initiatives.As part of the Customer Lab team, you will be leading data science analytics among Google’s advertising ecosystem partnering with customer Lab researchers and cross-functional senior leaders across Google’s Support, Product, Engineering, Brand, and business organizations to bring actionable insights to the business. You will develop an understanding of business objectives, risks, challenges, and opportunities to ensure that analytics efforts are supportive of business decision making and are actionable by executive leadership.The Go-To-Market Operations (GtM) team ensures Google's complex and ever-evolving Ads business runs smoothly. We are instrumental in setting go-to-market strategy, and ensuring flawless execution and operations against the strategy. We have teams embedded in each of the major Ads business areas as well as global teams that work across the business areas. Team members are analytical and strategic, with a pragmatic sense of how to get things done.The US base salary range for this full-time position is $146,000-$220,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. 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
Leverage critical thinking and problem statement definition, and decomposition to deliver impactful and actionable outcomes. Communicate and visualize insights to multiple levels of stakeholders with clarity, informing decision-making.Develop data engineering methodologies including data source and feature identification and integration, data pipelining, feature engineering, data wrangling, and analysis using script/code driven methods that can translate from research to production.Analyze and develop explanatory, predictive, and prescriptive models using appropriate mathematical methods including frequentist statistics, Bayesian statistics, time-series analysis, supervised and unsupervised machine learning methods, Natural Language Process (NLP), and semantic analysis.Develop and conduct experiments to validate findings from observational research.Ensure actionability of insights through internal and cross-functional collaboration.Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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