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Job Description: You have a Master's degree in a quantitative discipline such as Statistics, Engineering, Sciences, or equivalent practical experience, along with 4 years of experience using analytics to solve product or business problems, coding in languages like Python, R, SQL, and querying databases or conducting statistical analysis. Additionally, you prefer 6 years of experience in analytics, modeling, and analysis, with an understanding of statistics and data science applications. You are proficient in SQL, and have familiarity with Python or R. Your ability to translate complexity and explain analysis and methodologies to both engineering and business stakeholders is exemplary. You possess a keen understanding of business concepts, which you apply to decision frameworks and model development. Your partnering skills are excellent, and you can navigate ambiguity with ease. About The Job: You will be part of Google's BizOps team, where you will tackle challenging business problems selected by the leadership team. Working in small teams, you will collect and analyze data to derive insights and develop synthesized recommendations. You will have the opportunity to communicate your recommendations persuasively to senior-level executives, assist in driving implementation, and assess the impact of your suggestions. As a Business Data Scientist, you will play a pivotal role in shaping the incentives and future of the business. Your contributions will involve program development and continuous enhancement of your data science skills, exploring time series analysis, examining business drivers, and aiding in building the foundational infrastructure for business analytics and research. Responsibilities: - Incorporate business insights into incentives models, develop frameworks, driver models, and conduct analysis. - Develop statistical hypotheses and build predictive models. - Effectively build and work with complex datasets, creating and maintaining solutions using SQL, Python, or R. - Collaborate with business teams to influence program design and explain goal setting and investigative methodologies. - Engage with technical teams to integrate goals and other datasets into critical systems like Connect Sales.,
