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Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 8 years of experience with a Master's degree. Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 12 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). 5 years of experience in extracting and manipulating large datasets and designing ETL flows. About the jobHelp serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. The Business Platform for Sales and Support (BPSS) team is part of Enterprise Platforms and Ecosystems (EPE) within Corporate Engineering (CorpEng), with a mission to build products for Google's internal contact center business for sales and support. We are a fast-moving, high-impact team that operates like a startup, with the resources of Google behind us. As a Data Scientist on this team, you will work closely with product and engineering teams throughout the entire development process to help build and shape next-generation GenAI products for our users.Responsibilities Define, own, and evolve product success metrics, as well as report, analyze, and forecast key product trends to make recommendations for improvement. Perform data exploration to understand user behavior and identify opportunities for improving products. Apply technical expertise in observational data analysis, modeling, and causal inference to answer product questions. Lead the design, analysis, and interpretation of product experiments to measure the causal effects of product changes. Partner with Product, Engineering, and other cross-functional teams to influence, prioritize, and support product strategy. This involves framing and solving ambiguous business problems, acting as a thought partner, influencing a wide range of product and engineering stakeholders. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Master's degree in Statistics or Economics, a related field, or equivalent practical experience. 8 years of work experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of work experience with a PhD degree. Experience with statistical data analysis such as linear models, multivariate analysis, causal inference, or sampling methods. Experience with statistical software (e.g., SQL, R, Python, MATLAB, pandas) and database languages along with Statistical Analysis, Modeling and Inference. Preferred qualifications: Experience translating analysis results into business recommendations. Experience understanding potential outcomes framework and with causal inference methods (e.g., split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, matching estimators). Experience selecting tools to solve data analysis issues. Experience articulating business questions and using data to find a solution. Knowledge of structural econometric methods. About the jobAt Google, data drives all of our decision-making. Quantitative Analysts work all across the organization to help shape Google's business and technical strategies by processing, analyzing and interpreting huge data sets. Using analytical excellence and statistical methods, you mine through data to identify opportunities for Google and our clients to operate more efficiently, from enhancing advertising efficacy to network infrastructure optimization to studying user behavior. As an analyst, you do more than just crunch the numbers. You work with Engineers, Product Managers, Sales Associates and Marketing teams to adjust Google's practices according to your findings. Identifying the problem is only half the job; you also figure out the solution. Responsibilities Interact cross-functionally with a variety of leaders and teams, and work with Engineers and Product Managers to identify opportunities for design and to assess improvements for advertising measurement products. Collaborate with teams to define questions about advertising effectiveness, incrementality assessment, the impact of privacy, user behavior, brand building, bidding etc., and develop and implement quantitative methods to answer those questions. Work with large, complex data sets. Solve difficult, non-routine analysis problems, applying advanced analytical methods as needed. Conduct analyses that include data gathering and requirements specification, exploratory data analysis (EDA), model development, and delivery of results to business partners and executives. Build and prototype analysis pipelines iteratively to provide insights at scale. Develop knowledge of Google data structures, metrics, advocating for changes where needed for product development. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 5 years work experience with a Master's degree. Preferred qualifications: Advanced degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. Experience with conceptualizing and implementing scalable data pipelines. Experience with statistical packages (e.g., R, Python, etc.) to perform forecasting, segmentation, and classification. Knowledge of basic statistics and commonly used statistical methods (e.g., hypothesis testing, regression, cohort analysis, etc.). Strong data visualization skills, including building dashboards and visualizations for business reviews and executive-level presentations. About the jobHelp serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. Developer and Sustainability team’s mission is to apply data science to enable Geo in driving developer growth and planetary sustainability. We enable driven decision making across the Geo Makers organization (made up of Geo Developer and Geo Sustainability areas) to influence strategy, drive impact and unlock sustainable product growth.Responsibilities Lead the transformation of our self-serve analytics platform by introducing new metrics and drill downs to assist with self-serve diagnostics at scale, and driving integrations with GenAI tooling (NotebookLM, SQLMiner) to scale insight generation capabilities. Utilize technology to address new problem areas with segmentation analysis, recommender systems and GenAI applications. Build self-serve tooling and dashboarding to enable data driven decision making across the organization at scale. Collaborate on in-depth analytical projects, uncover insights and evaluate headroom to drive product enhancements which improve our developer experience. Surface insights around emerging markets (India and other APAC countries) that help teams understand users and guide global data improvement strategy. Design, execute and analyze experiments to evaluate growth levers and regional launches. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics or equivalent practical experience. 5 years of experience in designing, installation, and managing database products. 5 years of coding experience in shell scripting, Go, Python, C, C++, or Java. Experience with Linux and SQL. Preferred qualifications: Experience in coding with Advanced Business Application Programming (ABAP). Experience in administering SAP Business Suite in HA and DR environments, Cloud Connector and integration platforms (e.g., PI/PO, SDI, DS, etc.), and automation for SAP patching. Experience with customer support platforms. Ability to analyze and resolve difficult technical issues quickly in a changing environment. About the jobDatabase Administrators embrace Google's motto to ensure millions of users can access the world's information without a glitch. As a Database Engineer at Google, you design, implement and maintain our relational database systems for performance and reliability. You're responsible for tuning and configuring our databases as well as building tools and scripts to monitor, troubleshoot and automate our systems. You propose test plans and interface with external groups, developers and application owners to arrive at optimal solutions. Other areas of responsibility include designing and enhancing disaster recovery and backup systems. As you are writing automation for hundreds of machines, pages are serving up in real time, which means that the user has a seamless browsing experience.With your technical expertise, you design, implement and improve processes, procedures and automation for all database-centric areas. You also test the systems in place and interface with external groups. Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Engineer and run SAP infrastructure to meet performance, security, high availability, scalability, and other requirements. Interact with business analysts and developers to ensure the overall infrastructure design of business applications meets requirements of performance, security and high availability. Perform operational Data Base Engineering (DBE) duties in a complex environment, including patching, environments cloning, database and application upgrades, implementing backup and monitoring procedures. Analyze performance issues in the application and database tiers of SAP installations. Assist developers with performance tuning. Work with third-party vendor products teams (e.g., SAP and partners) to resolve any issues. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

您將作為數據團隊的一員，負責解析和分析大型數據集，尋找並獲取新的數據來源，並與Alpha和策略研究團隊合作，構建預測性的機器學習模型。此職位僅接受具有量化背景的候選人，不考慮科技或金融科技背景。 要求 - 具有相關技術學科的學歷（如計算機科學、數學、統計學、物理學等）。 - 具備統計分析和大型數據集管理經驗。 - 熟悉Linux、Bash、Python和SQL數據庫。 - 能夠獨立工作並完成項目，快速學習新系統，具有創造性思維，並注重細節。 福利 - 具有競爭力的薪酬，並有機會獲得豐厚的獎勵。 - 在協作友好的環境中工作，並參與決策過程。