Business and Marketing Data Scientist, Behavioral Economics
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Minimum qualifications:
- Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience.
- 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis.
- Experience with analyzing machine learning model performance or working on LLMs.
Preferred qualifications:
- 6 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 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.
In this role, you will use data to identify opportunities for Google to operate more efficiently, from enhancing advertising efficacy to improving the understanding of user behavior. You will work with a multi-disciplinary team of data scientists, engineers, product managers, sales associates, and marketing teams to adjust Google's practices according to findings. You will work on multiple projects concurrently, developing datasets, analyses, models, and methods to support and verify the impact of recommendations.
The US base salary range for this full-time position is $166,000-$244,000 + 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
- Develop metrics to track and evaluate solution deployment across teams.
- Create dashboards and tools to automate processes, generate reports, and guide product decisions.
- Curate and validate data to ensure quality standards are met.
- Collaborate with stakeholders to understand the domain, business goals, and data infrastructure context.
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