Staff Business Data Scientist, Google Customer Solutions
- linkCopy link
- emailEmail a friend
Minimum qualifications:
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
- 7 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
- Experience with building machine learning models using libraries such as TensorFlow and PyTorch.
- Experience in designing and implementing causal inference methods (e.g., A/B testing, difference-in-differences, synthetic control, instrumental variables) is essential.
Preferred qualifications:
- 9 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
About the job
Google's leadership team hand-picks thorny business issues, 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. The US base salary range for this full-time position is $197,000-$291,000 + 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
- Design, develop, and validate causal inference models (e.g., Synthetic Control, Difference-in-Differences, Double Machine Learning) to accurately isolate and measure the true incremental impact of GCS programs and interventions.
- Serve as the team's subject matter expert on Causal Inference and advanced measurement, consulting with Product, Engineering, and Business leaders to translate questions into testable hypotheses and rigorous designs.
- Stay current with the latest academic and industry research in Causal ML, Deep Learning, and Econometrics, proactively proposing and prototyping new methods.
- Partner with stakeholders to design rigorous A/B tests and randomized control trials (RCTs) when feasible, and define the metrics and success criteria for each study.
Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy.
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.
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form.
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.