Data Scientist, Research, Search Platforms

Job Description

Role Overview:At Google, data drives all decision-making processes. As a Quantitative Analyst, you will play a crucial role in shaping Googles business and technical strategies by processing, analyzing, and interpreting vast data sets. Utilizing analytical excellence and statistical methods, you will sift through data to identify opportunities for Google and its clients to operate more efficiently. You will collaborate with various teams to adjust practices based on your findings, contributing to enhancing advertising efficacy, network infrastructure optimization, and understanding user behavior.Key Responsibilities:- Solve analysis problems, conduct analysis, gather data, specify requirements, deliver ongoing insights, and make presentations.- Build and prototype analysis pipelines to provide insights at scale, developing a comprehensive understanding of Googles data structures and metrics.- Interact cross-functionally with diverse teams, working with engineers to identify design opportunities and assess product improvements.- Make business recommendations (e.g., cost-benefit analysis, forecasting, experiment analysis) through visual displays of quantitative information to stakeholders at various levels.- Research and develop analysis, forecasting, and optimization methods to enhance the quality of Googles user-facing products.Qualifications Required:- Masters degree in Statistics or Economics, a related field, or equivalent practical experience.- 10 years of experience in data science, statistics, or in a computational biologist/bioinformatician role.- Experience with statistical data analysis like linear models, multivariate analysis, causal inference, or sampling methods.- Proficiency in statistical software such as SQL, R, Python, MATLAB, pandas, and database languages for Statistical Analysis, Modeling, and Inference.- Experience translating analysis results into business recommendations.- Knowledge of causal inference methods like split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, and matching estimators.- Ability to select tools to address data analysis challenges.- Articulate business questions and utilize available data to find solutions.- Familiarity with structural econometric methods.(Note: The Additional details of the company were not explicitly mentioned in the provided job description.) Role Overview:At Google, data drives all decision-making processes. As a Quantitative Analyst, you will play a crucial role in shaping Googles business and technical strategies by processing, analyzing, and interpreting vast data sets. Utilizing analytical excellence and statistical methods, you will sift through data to identify opportunities for Google and its clients to operate more efficiently. You will collaborate with various teams to adjust practices based on your findings, contributing to enhancing advertising efficacy, network infrastructure optimization, and understanding user behavior.Key Responsibilities:- Solve analysis problems, conduct analysis, gather data, specify requirements, deliver ongoing insights, and make presentations.- Build and prototype analysis pipelines to provide insights at scale, developing a comprehensive understanding of Googles data structures and metrics.- Interact cross-functionally with diverse teams, working with engineers to identify design opportunities and assess product improvements.- Make business recommendations (e.g., cost-benefit analysis, forecasting, experiment analysis) through visual displays of quantitative information to stakeholders at various levels.- Research and develop analysis, forecasting, and optimization methods to enhance the quality of Googles user-facing products.Qualifications Required:- Masters degree in Statistics or Economics, a related field, or equivalent practical experience.- 10 years of experience in data science, statistics, or in a computational biologist/bioinformatician role.- Experience with statistical data analysis like linear models, multivariate analysis, causal inference, or sampling methods.- Proficiency in statistical software such as SQL, R, Python, MATLAB, pandas, and database languages for Statistical Analysis, Modeling, and Inference.- Experience translating analysis results into business recommendations.- Knowledge of causal inference methods like split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, and matching estimators.- Ability to select tools to address data analysis challenges.- Articulate business questions and utilize available data to find solutions.- Familiarity with structural econometric methods.(Note: The Additional details of the company were not explicitly mentioned in the provided job description.)

Keyskills :
data sciencestatisticscomputational biologybioinformaticsstatistical data analysislinear modelsmultivariate analysiscausal inferenceSQLPythonMATLABStatistical AnalysisModelingsampling methodspandasInferencetranslating analysis results in