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**Job Description:** **Role Overview:** As a Data Scientist at Google, you will play a crucial role in providing quantitative support, market understanding, and a strategic perspective to partners across the organization. Your expertise in analytics will enable you to assist your colleagues in making informed decisions based on data insights. By leveraging your skills in statistical analysis and coding, you will contribute to the development of impactful machine learning models for business applications. **Key Responsibilities:** - Define and report Key Performance Indicators (KPIs) to senior leadership during regular business reviews, contributing to metric-backed annual Objective and Key Results (OKR) setting. - Generate hypotheses to enhance the performance of AI products by researching and implementing advanced techniques such as prompt engineering, in-context learning, and reinforcement learning. - Design and implement machine learning strategies for data enrichment, including the development of autoencoder-based latent variables and complex heuristics. - Develop variance reduction and simulation strategies to improve the reliability of experiments with limited sample sizes. - Translate business challenges into unsupervised and supervised machine learning modeling problems, building prototypes to validate hypotheses of business impact. **Qualifications Required:** - Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. - 5 years of work experience in analysis applications and coding languages such as Python, R, and SQL (or 2 years of experience with a Master's degree). - Experience in developing deep learning models for business impact and debugging throughput and latency issues in AI. - Proficiency in handling large-scale data transformation pipelines for batch inference of machine learning models. (Note: Preferred qualifications include a Master's degree in a relevant field and 5 years of experience in analysis applications and coding.) (Note: The job description also includes details about Google's Data Science team's mission to transform enterprise operations with AI and advanced analytics, as well as the collaborative efforts with Research and Machine Learning Infrastructure teams.) **Job Description:** **Role Overview:** As a Data Scientist at Google, you will play a crucial role in providing quantitative support, market understanding, and a strategic perspective to partners across the organization. Your expertise in analytics will enable you to assist your colleagues in making informed decisions based on data insights. By leveraging your skills in statistical analysis and coding, you will contribute to the development of impactful machine learning models for business applications. **Key Responsibilities:** - Define and report Key Performance Indicators (KPIs) to senior leadership during regular business reviews, contributing to metric-backed annual Objective and Key Results (OKR) setting. - Generate hypotheses to enhance the performance of AI products by researching and implementing advanced techniques such as prompt engineering, in-context learning, and reinforcement learning. - Design and implement machine learning strategies for data enrichment, including the development of autoencoder-based latent variables and complex heuristics. - Develop variance reduction and simulation strategies to improve the reliability of experiments with limited sample sizes. - Translate business challenges into unsupervised and supervised machine learning modeling problems, building prototypes to validate hypotheses of business impact. **Qualifications Required:** - Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. - 5 years of work experience in analysis applications and coding languages such as Python, R, and SQL (or 2 years of experience with a Master's degree). - Experience in developing deep learning models for business impact and debugging throughput and latency issues in AI. - Proficiency in handling large-scale data transformation pipelines for batch inference of machine learning models. (Note: Preferred qualifications include a Master's degree in a relevant field and 5 years of experience in analysis applications and coding.) (Note: The job description also includes details about Google's Data Science team's mission to transform enterprise operations with AI and advanced analytics, as well as the collaborative efforts with Research and Machine Learning Infrastructure teams.)
