Location: Chicago, IL
Cap-Exempt H-1B Position — No lottery required
Applicants in the County of Los Angeles: Qualified applications with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Note: By applying to this position you will have an opportunity to share your preferred working location from the following: **Mountain View, CA, USA; Chicago, IL, USA; Irvine, CA, USA; New York, NY, USA**. ### **Minimum qualifications:** - Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience. - 3 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree. - Experience working with Large Language Models, prompt engineering, and fine-tuning techniques. ### **Preferred qualifications:** - 4 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or a relevant PhD degree. - Experience with vector databases, embedding models, transformer models, and clustering algorithms. ## **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. Our team, within Go-to-Market (GTM), serves as the strategic intelligence partner for product teams, transforming massive volumes of unstructured conversational data into quantified, trusted insights that bridge the gap between customer feedback and product