Senior Data Scientist/Research Economist
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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.
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.
- Experience working with text data (embeddings, LLM classification, etc.).
- Experience investigating questions in labor economics, industrial organization, or technology diffusion.
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.
Google's AI & Economy program is a high-priority, cross-functional initiative focused on producing research, engaging top academics and policymakers, and building new data products to understand AI's economic impact. We are expanding our ambition to establish Google as a leading voice in the public AI & Economy conversation.
We are seeking a creative, intellectually curious and highly motivated Economists/Data Scientist to join the Economics team to design and deliver this marquee project on measuring and communicating to the world the economically meaningful AI usage in Google products, its implications for the wider economy, and support our research efforts more widely.
Responsibilities
- Design and conduct research on the economic impacts of AI technologies by pioneering novel datasets and empirical methodologies.
- Develop new conceptual frameworks and taxonomies to systematize ways in which users and businesses engage with AI products, drawing as needed on existing economic research and input from academic advisors.
- Communicate the research findings externally through high-impact research publications, media articles, and stakeholder presentations.
- Position Google at the forefront of economic AI research by building strategic partnerships with external academic partners, global policy bodies and think tanks, and leverage these partnerships to improve our research and amplify its impact on evidence-based policymaking.
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