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Astera Labs (NASDAQ: ALAB) provides rack-scale AI infrastructure through purpose-built connectivity solutions. By collaborating with hyperscalers and ecosystem partners, Astera Labs enables organizations to unlock the full potential of modern AI. Astera Labs’ Intelligent Connectivity Platform integrates CXL®, Ethernet, NVLink, PCIe®, and UALink™ semiconductor-based technologies with the company’s COSMOS software suite to unify diverse components into cohesive, flexible systems that deliver end-to-end scale-up, and scale-out connectivity. The company’s custom connectivity solutions business complements its standards-based portfolio, enabling customers to deploy tailored architectures to meet their unique infrastructure requirements. Discover more at www.asteralabs.com.Job Description Astera labs is seeking a skilled and motivated Data Scientist. This individual will play a pivotal role in identifying key data points for collection, developing strategies to accumulate data and deriving actionable insights an anomaly based on a solid foundation of relevant know-how. Also, will also be responsible for creating, testing, and deploying scripts and methods for data collection and analysis to support decision-making. The Engineer will collaborate with cross-functional teams to identify critical data sources to determine the most effective data collection strategies, will develop automated and scalable data collection pipelines, will ensure data quality, integrity, and consistency across all sources and may use AI techniques to refine the results toward failures predictions. Basic Qualifications Bachelor’s degree in computer science, Data Science, Engineering, Mathematics, or a related field. Advanced degrees in data science or Machine learning / AI - Advance. Proficiency in programming languages such as Python, R, or MATLAB. Strong understanding of data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Understanding of high speed interfaces such as Ethernet, PCI-E , WiFi. Experience with data visualization tools such as Tableau, Matplotlib, Graphana. Strong analytical and critical-thinking skills to identify patterns and outliers. Customer-obsession, Think and act with the customer in mind! Goal-driven, Self-motivated, be able to work independently and with teams with people around the globe. Entrepreneurial, open-minded behavior and can-do attitude. Required Experience Experience with data manipulation and analysis tools (e.g., Pandas, NumPy, SQL). Machine learning and AI techniques and frameworks (e.g., TensorFlow, Scikit-learn). Proven ability to manage multiple tasks and meet deadlines. Preferred Experience Embedded Firmware development with C-language, scripting with Python or other equivalent programming languages. Master’s degree in a relevant field. Experience with cloud platforms (e.g., AWS, Azure, GCP) for data storage and processing. Familiarity with big data technologies (e.g., Hadoop, Spark). Knowledge of engineering design tools and processes. We know that creativity and innovation happen more often when teams include diverse ideas, backgrounds, and experiences, and we actively encourage everyone with relevant experience to apply, including people of color, LGBTQ+ and non-binary people, veterans, parents, and individuals with disabilities.

Minimum qualifications: Bachelor's degree or equivalent practical experience. 3 years of experience in a data engineering, data infrastructure, or data analytics role. Experience with database administration techniques or data engineering, as well as writing software in Java, C++, Python, Go, or JavaScript. Preferred qualifications: Experience with data warehouses, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments. Experience with data analysis, including statistics, and ML model development (data preparation, model selection, evaluation, tuning). Experience in scripting languages like Python for data manipulation, analysis, and automation. Ability to monitor, troubleshoot, and tune data systems and pipelines to improve efficiency. Ability to develop tools and systems to automate data processes, and increase overall efficiency, with proficiency in programming languages (e.g., SQL, Python), producing readable and well-structured code. Ability to deliver and maintain data projects from conception to production. About the job Google Play provides apps, games, and digital content services that bring Android devices to life. The Play Store serves over four billion users around the world, and is a critical driver of Google’s overall business growth. The Play Data Science and Analytics (DSA) team works on a variety of challenging data science projects to drive product and go-to-market decisions for Play. Our goal is to Power Play’s growth by building a deep understanding of our users and developers, enabling data-driven decision making, through insights, thought leadership, and unified data foundations.As a Data Engineer on the Play Data Science and Analytics team, you will take a significant role in designing and building the next generation of our data infrastructure. You will be responsible for architecting, implementing, and optimizing complex, scalable data pipelines, moving beyond basic development to own key components of our data warehouse. This role requires a technical expert who can manage massive datasets, write highly efficient SQL and Python code, and collaborate effectively with senior stakeholders and engineers. You will build innovative data foundations and AI-driven insights solutions while helping to define the standards and best practices that elevate the entire team, driving data quality and AI-readiness initiatives. Responsibilities Design, build, and maintain scalable data pipelines to ingest, process, and store data from various sources. Implement data quality checks and monitoring to ensure accuracy and integrity. Write complex SQL queries for data extraction and transformation to enable ad-hoc analysis and automated reporting. Conduct quantitative analysis to support business decisions. Develop and manage scalable data foundations and models specifically designed to support AI/ML initiatives and AI-driven insights. Develop, test, and deploy intelligent agents using Python and the Google ADK framework to automate tasks like data analysis and system orchestration. Partner with executive stakeholders and data scientists. 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, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative 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: PhD in a quantitative field. 10 years of experience with statistical data analysis such as linear models, multivariate analysis, stochastic models, and sampling methods. 5 years of leadership experience, including people management. Experience with Machine Learning (ML) on large datasets, with the ability to select the right statistical tools in a given data analysis problem. Understanding of potential outcomes framework and with causal inference methods such as split-testing, instrumental variables, difference-in-difference methods, fixed effects regression, panel data models, regression discontinuity, matching estimators, with knowledge of structural econometric methods. Ability to set and drive technical strategy. About the jobAs a Technical Lead on Google’s Advertising Measurement team, you will apply scientific aptitude, excellence, precision, accuracy, expertise, thoroughness and statistical expertise to navigate the complex challenges of a global, privacy-preserving advertising ecosystem. Google is a pioneer in sustaining an open internet through a mutually-reinforcing cycle of ad-planning, optimization, and measurement; in this strategic leadership role, you will be the recognized authority driving that cycle forward. You will develop, organize, and launch large-scale projects spanning engineering and analysis across Search, Display, YouTube, and beyond. By translating advanced science specifically causal inference and quantitative methodologies into deployed products, you will lead the charge in defining paradigm-shifting measurement standards for the future of digital advertising. Working cross-functionally with Engineers, Product Managers, and Sales, you will adjust global strategies based on your findings, ensuring advertising remains useful for users and results-driven for publishers. We are seeking quantitatively trained experts with a passion for business strategy and a deep appreciation for consumer behavior. In this role, you won’t just improve products; you will empower an exceptional team to shape the marketing-technology industry globally. If you thrive in fluid, science-driven environments and are ready to leverage data and technology to solve modern advertising’s greatest challenges, your leadership will be the catalyst for the next era of innovation.Responsibilities Apply causal inference and differential privacy methods to design experiments, assess attribution, and develop privacy-preserving marketing products. Execute end-to-end analyses including data gathering, EDA, and model development to deliver strategic insights to executives. Build iterative analysis pipelines and prototype data structures to provide scalable insights across Google’s complex data ecosystems. Collaborate with Product and Engineering team to define and answer quantitative questions regarding incrementality, user behavior, and bidding optimization. Provide technical guidance and prioritization for the team, conduct cost-benefit analyses to drive high-level business decisions and product strategy. 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.

▋▍About Us｜關於我們（醫療 X 科技） 用數據驅動決策，將生醫資訊轉化為生命的價值。 在慧康生技（Health2Sync），數據是我們最核心的資產。身為數據團隊的一員，你將有機會處理海量且多樣化的生醫數據（Biomedical Data），並透過機器學習與生成式 AI 技術，將其轉化為對用戶及醫療院所有實質幫助的數據產品。 我們不僅僅是技術的執行者，更是公司重大決策的參與者。在這裡，每一份分析報告都可能改變產品走向，每一條數據管線都在支撐全球百萬用戶的健康。期待對數據科學充滿熱忱的你加入，與我們一起用技術為病患與醫療人員創造更多可能性。 ▋▍Why Join Us｜為什麼加入我們 接觸稀缺的生醫大數據：處理真實世界（Real-World Data）的生理指標與健康數據，在技術深度之外，累積珍貴的醫療科技領域知識（Domain Know-how）。GenAI 與 LLM 實戰舞台：不只是開發傳統模型，你將主導基於大語言模型的應用開發，將最新的 AI 技術落地於數位健康場景。從基礎設施到產品落地：參與 Data Lakehouse 的架構設計與優化，親手建立支撐大規模運算與建模的高效率數據管線。高度影響力的決策參與：團隊推崇透明溝通與共創，你的分析結果與模型表現將直接影響產品的發展策略與商業方向。 ▋▍Role Highlights｜職缺亮點 數據科學的最前線：同時跨足數據工程與 AI 建模，讓你成為市面上最搶手的全方位數據專才。賦予數據生命感：看著你寫出的模型轉化為 App 上的健康建議，實質改善病患生活，這種成就感無可取代。純技術、零官僚：我們在乎的是數據的真實性與解決方案的有效性，提供最透明、最尊重專業的工程環境。接軌國際技術標準：與具備國際視野的團隊共事，使用最先進的數據架構處理跨國市場的挑戰。 ▋▍Responsibility｜主要職責 [ 數據基礎設施建構 ] 架構建立與維護：設計並持續優化數據基礎設施（Data Pipeline, Data Lakehouse），以支援高效的數據分析與機器學習建模。管線自動化：使用 Airflow/Dagster 構建穩定、可擴展的 Data Pipeline，並管理大數據儲存架構（如 Apache Iceberg）。 [ AI 與機器學習應用開發 ] 模型開發與部署：利用數位健康數據開發並部署機器學習、統計模型及生成式 AI (GenAI) 應用。LLM 應用實踐：針對產品需求，構建並維護基於大語言模型 (LLM) 的應用服務，提升產品智能化程度。系統性能優化：優化現有的 AI 系統與演算法，確保其在生產環境中的性能與可擴展性。 [ 數據決策支援 ] 跨團隊任務執行：運用分析工具與統計方法，支援產品與業務團隊的特定任務，將數據轉化為可執行的行動建議。數據專案推動：參與數據產品發想，持續探索能優化 H2 產品體驗的數據科學方案。 ▋▍Media Coverage｜媒體報導 《環球生技月刊》慧康生技明掛牌興櫃 《今周刊》打造智抗糖 App 攻入慢性病平台 《數位時代》台灣新創進軍韓國 《今周刊》慧康創業背景 《天下雜誌》台灣第一數位療法

WorldQuant develops and deploys systematic financial strategies across a broad range of asset classes and global markets. We seek to produce high-quality predictive signals (alphas) through our proprietary research platform to employ financial strategies focused on market inefficiencies. Our teams work collaboratively to drive the production of alphas and financial strategies – the foundation of a balanced, global investment platform. WorldQuant is built on a culture that pairs academic sensibility with accountability for results. Employees are encouraged to think openly about problems, balancing intellectualism and practicality. Excellent ideas come from anyone, anywhere. Employees are encouraged to challenge conventional thinking and possess an attitude of continuous improvement. Our goal is to hire the best and the brightest. We value intellectual horsepower first and foremost, and people who demonstrate an outstanding talent. There is no roadmap to future success, so we need people who can help us build it. The Role: We are seeking an exceptionally talented data scientist with strong modeling and programming skills to join our team. In this role, you will work closely with data science team and technologists across the firm to develop appropriate features and metrics for data processing. Perform analysis and generate models of financial datasets using machine learning techniques Process, clean and verify the integrity of unstructured data and turn data into valuable insights Develop and create data that seek to predict the movement of financial market Transfer data into internal infrastructure applying variety of algorithmic techniques What You’ll Bring: Have a Master’s degree or higher from a leading university in Computer Science, Electrical Engineering or other related areas Good academic record Familiar with modeling, data structures, algorithms and optimizations Strong knowledge of machine/deep learning algorithms Proficient in programming languages of both C++ and Python Possess good communication and presentation skills in English Ability to work independently and as member of a team Research scientist mindset: deep thinker, creative, strong work ethic, persevering, smart a self-starter Detail oriented and capable of multitasking and delivering in fast-paced work environment As a plus: While not mandatory, a strong interest in financial markets will definitely be beneficial Participant of ACM-ICPC By submitting this application, you acknowledge and consent to terms of the WorldQuant Privacy Policy. The privacy policy offers an explanation of how and why your data will be collected, how it will be used and disclosed, how it will be retained and secured, and what legal rights are associated with that data (including the rights of access, correction, and deletion). The policy also describes legal and contractual limitations on these rights. The specific rights and obligations of individuals living and working in different areas may vary by jurisdiction. Copyright © 2025 WorldQuant, LLC. All Rights Reserved.WorldQuant is an equal opportunity employer and does not discriminate in hiring on the basis of race, color, creed, religion, sex, sexual orientation or preference, age, marital status, citizenship, national origin, disability, military status, genetic predisposition or carrier status, or any other protected characteristic as established by applicable law.

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. 3 years of experience as a people manager within a technical leadership role. Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 4 years of experience as a people manager within a technical leadership role. Experience with developing machine learning models (supervised and unsupervised), launch experiments (A/B Testing), and end-to-end data infra and analytics pipelines. Experience in developing new models, methods, analysis and approaches, and with classification and regression, prediction and inferential tasks, training/validation criteria for ML algorithm performance. Prior business knowledge and understanding of monetization. About the jobGoogle Play provides apps, games, and digital content services that bring Android devices to life. The Play Store serves over four billion users around the world, and is a critical driver of Google’s overall business growth.As the Play Data Science and Analytics team, we work on a variety of challenging data science projects to drive product decisions for Play. This team is truly embedded in the product development lifecycle: we're thought partners from strategy shaping and project ideation to experimentation and launches.The Platforms and Devices team encompasses Google's various computing software platforms across environments (desktop, mobile, applications), as well as our first party devices and services that combine the best of Google AI, software, and hardware. Teams across this area research, design, and develop new technologies to make our user's interaction with computing faster and more seamless, building innovative experiences for our users around the world.Responsibilities Synthesize complex insights across key domains (payments/FOP performance and retailing/ buyer activations) to shape product roadmaps, optimize purchase flows, and identify high-value opportunities. Define product success metrics, design advanced experimentation frameworks, and build scalable measurement views to ensure robust data integrity and proper logging. Direct and mentor a team of 5 Product Data Scientists, managing team roadmaps, resource allocation, and technical execution aligned with long-term goals. Partner with local Play BI, Play Apps and Games teams counterparts to foster a thriving local Data Science and Analytics community. Act as a critical thought partner to Product Management, Engineering, and Strategy teams, translating quantitative findings into actionable features and performance-measurement standards. 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.

Req ID: 135134Remote Position: YesRegion: AsiaCountry: IndiaState/Province: ChennaiCity: Guindy, ChennaiSummaryThe AI Data Analyst will design, develop, document, and maintain data pipelines and architectures, working closely with IT, Data Engineering, and Data Science teams to deliver artificial intelligence and machine learning solutions. Provide technical support on selected AI systems (for example, Generative AI applications, agentic workflows, and internal data integration tools) and participate in enterprise IT and AI projects.Detailed DescriptionPerforms tasks such as, but not limited to, the following:•Collaborate with IT and Data Science teams to gather technical requirements, ensuring data availability and system readiness for AI integration.•Design, build, and optimize data pipelines (ETL/ELT) to prepare, clean, and structure datasets for machine learning models and large language models (LLMs).•Work within Google Cloud environments to manage datasets, orchestrate data flows, and support model deployment.•Respond to system, API, and data pipeline problems by troubleshooting data anomalies, analyzing logs, and determining the technical course of action.•Develop and maintain technical documentation for data architectures, API integrations, and AI workflows.•Participate in the configuration, testing, and deployment of agentic AI development and workflow orchestration platforms.Knowledge/Skills/Competencies•Strong technical collaboration and teamwork skills within an IT environment.•Good analytical, technical, troubleshooting, and problem-solving skills.•Good technical documentation skills, including mapping technical architectures, data pipelines, and system integrations.•Good understanding of data engineering concepts, database management, and the IT software development life cycle.•Proficient coding skills in Python (including data libraries like Pandas and NumPy) and robust SQL skills for complex database querying and data manipulation.•Understanding of core machine learning concepts and familiarity with Generative AI tools, agentic development, and AI orchestration platforms (e.g., Flowise AI, Zapier, n8n).•Familiarity with Google Cloud data and AI technologies, specifically Gemini, BigQuery, and Vertex AI.•Understanding of interrelations between IT infrastructure components (cloud environments, APIs, databases, data pipelines, servers, etc.).• Physical Demands• Duties of this position are performed in a normal office environment.• Duties may require extended periods of sitting and sustained visual concentration on a computer monitor or on numbers and other detailed data. Repetitive manual movements (e.g., data entry, using a computer mouse, using a calculator, etc.) are frequently required.Typical Experience•Minimum 3+ years of professional experience required .•1 to 3 years of relevant experience in similar rolesTypical Education•Bachelors Degreeor consideration of an equivalent combination of education and experience.•Educational Requirements may vary by GeographyNotesThis job description is not intended to be an exhaustive list of all duties and responsibilities of the position. Employees are held accountable for all duties of the job. Job duties and the % of time identified for any function are subject to change at any time.Celestica is an equal opportunity employer. All qualified applicants will receive consideration for employment and will not be discriminated against on any protected status (including race, religion, national origin, gender, sexual orientation, age, marital status, veteran or disability status or other characteristics protected by law).At Celestica we are committed to fostering an inclusive, accessible environment, where all employees and customers feel valued, respected and supported. Special arrangements can be made for candidates who need it throughout the hiring process. Please indicate your needs and we will work with you to meet them.COMPANY OVERVIEW:Celestica (NYSE, TSX: CLS) enables the world’s best brands. Through our recognized customer-centric approach, we partner with leading companies in Aerospace and Defense, Communications, Enterprise, HealthTech, Industrial, Capital Equipment and Energy to deliver solutions for their most complex challenges. As a leader in design, manufacturing, hardware platform and supply chain solutions, Celestica brings global expertise and insight at every stage of product development – from drawing board to full-scale production and after-market services for products from advanced medical devices, to highly engineered aviation systems, to next-generation hardware platform solutions for the Cloud.Headquartered in Toronto, with talented teams spanning 40+ locations in 13 countries across the Americas, Europe and Asia, we imagine, develop and deliver a better future with our customers.Celestica would like to thank all applicants, however, only qualified applicants will be contacted.Celestica does not accept unsolicited resumes from recruitment agencies or fee based recruitment services.

At Google, we have a vision of empowerment and equitable opportunity for all Aboriginal and Torres Strait Islander peoples and commit to building reconciliation through Google’s technology, platforms and people and we welcome Indigenous applicants. Please see our Reconciliation Action Plan for more information.Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field, or equivalent practical experience. 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 5 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. Experience in collaborating with engineers, product managers on product-centric insights. Excellent Python/R programming skills. Excellent communication or presentation skills. About the jobGoogle Photos is a photo sharing and storage service developed by Google. Photos is one of the most sought after products at Google and is looking for both client-side (web and mobile), with server-side (search, storage, serving) and machine intelligence (learning, computer vision) Software Engineers. We are dedicated to making Google experiences centered around the user.Responsibilities Analyze user trends utilizing related tools (e.g., SQL, R, Python). Help to solve problems, narrow down multiple options into the best approach, and take ownership of open-ended business problems to reach an solution. Build new processes, procedures, methods, tests, and components with foresight to anticipate and address future issues. Define and report on Key Performance Indicators (KPIs) to align business direction with the cross-functional/organizational leadership team. Translate analysis results in business insights or product improvement opportunities. Identify growth opportunities for the product and business through analysis, insights and communication. Collaborate across teams to align resources and direction. 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, a related quantitative field, or equivalent practical experience. 8 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL), or 5 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. 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). Experience in product analytics within payments, e-commerce, or financial services. Ability to take initiative in unstructured environments with a bias for action and sharp attention to detail. 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. As a Product Data Scientist for FOP Optimization, you will shape Payments products and solutions, helping our leaders make data-driven decisions. You will lead a critical part of the payments routing infrastructure, Smart Router, that utilizes machine learning and AI to process first-party transactions across Play, YouTube, Ads, and more. You will drive analytics for the form of payment (FOP) optimization, building on success metrics, driving insights, and driving global launches. You will also play a critical role in our interactions on Business-to-Consumer (B2C) analytics with Play and YouTube to optimize buyflows, purchase readiness, conversion, and UI on these critical Google products.Responsibilities Play a critical role in shaping the future of Google Payments by leveraging data and analytics to drive decisions, influencing strategy, and creating business impact across the organization. Identify and solve ambiguous, high-stakes problems, transforming data into clear insights that directly influence leadership decisions (e.g., VPs and directors). Lead complex projects that combine analytical precision with organizational strategy, delivering clear insights that inform tangible business decisions. Contribute to the development and alignment of team objectives and key results and analytics strategy to ensure they support broader product and business goals across the Payments organization. Collaborate cross-functionally with product, engineering, and operations teams to define key metrics and support data-driven decision making. 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. 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 2 years work experience with a Master's degree). Preferred qualifications: Master's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 5 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL). Strong understanding of digital advertising measurement concepts, including attribution modeling, incrementality testing, and media mix modeling (MMM). Excellent communication and presentation skills with the ability to influence stakeholders. 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. Measurement is a cornerstone of performance advertising, driving the majority of Google Ads business growth. Accurate and unbiased measurement empowers bidding engines to maximize advertiser ROI, fostering growth for both advertisers and Google. The Product Analyst team applies advanced analytics to guide Google Ads strategy in this crucial area, ensuring that the advertising solutions effectively connect businesses with customers and deliver measurable results across the various ad platforms.Responsibilities Collaborate with Product Managers, Engineers, and Research Scientists to define and track key performance indicators (KPIs) for Google Ads measurement products. Conduct in-depth analysis of large datasets to identify trends, patterns, and insights that inform product strategy and development. Communicate complex data and analysis in a clear and concise manner to various stakeholders, including product leadership, engineering teams, and business partners. Execute defined, moderately difficult analytical tasks under guidance from the manager or team member/team lead. For straightforward problems, execute end-to-end analysis with minimal guidance. 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.