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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.

▋▍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. 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 of 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. 8 years of work experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL). 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. Responsibilities Perform analysis utilizing relevant tools (e.g., SQL, R, Python). Using specialized knowledge, use custom data infrastructure or existing data models, as appropriate. Provide analytical insights and recommendations to influence the development of overall, long-term product development strategies in collaboration with the leadership team for a product/business area or the executives at a partner organization. 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. 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 return on investment, 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.

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 a candidate to join our team as a Data Engineer. The Data Engineer will partner with our close-knit team of quantitative researchers, technologists and data sourcing colleagues to analyze and enrich a broad range of structured and unstructured large-scale data. Job responsibilities include, but not limited to the followings: Enriching a wide range of structured and unstructured data into datasets for quantitative analysis and financial engineering. Enhancing data quality integrity by developing validation tools to measure the effectiveness of data enrichment. Becoming a domain expert on different deep learning and machine earning applications, analyzing understanding the underlying dynamics and behaviors within the data. Develop insights based on the data and collaborate with the research team to generate signals. Developing the utility tools that can further automate the software development, testing and deployment workflow. What You’ll Bring: Strong academic background – minimum of a bachelor’s degree in a technical or quantitative field. Practical experience with and understanding of deep neural networks and other machine learning techniques. Demonstrated ability to implement data science pipelines and real-time applications in Python 3+ years of relevant experience as a Data Engineer or similar roles. Proficiency with python-based tools like Jupyter notebook, coding standards like pep8. Experience with LLM/AI for data processing is a plus Exceptional analytical problem-solving abilities, with a strong attention to detail. Good command of English Excellent software development skills: ability to convert rough overall use-cases to a working codebase.\ Motivated by a deep curiosity and passion to learn is a plus. Past experience as a data scientist or data engineer in finance or investment profile is a plus. Experience with Linux/Unix shell and Git is a plus. 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.

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 for a candidate to join our team as a Data Engineer. The Data Engineer will partner with our close-knit team of quantitative researchers, technologists and data sourcing colleagues to analyze and enrich a broad range of structured and unstructured large-scale data. Job responsibilities include, but not limited to the followings: Enriching a wide range of structured and unstructured data into datasets for quantitative analysis and financial engineering. Enhancing data quality integrity by developing validation tools to measure the effectiveness of data enrichment. Becoming a domain expert on different deep learning and machine earning applications, analyzing understanding the underlying dynamics and behaviors within the data. Develop insights based on the data and collaborate with the research team to generate signals. Developing the utility tools that can further automate the software development, testing and deployment workflow. What You’ll Bring: Strong academic background – minimum of a bachelor’s degree in a technical or quantitative field. Practical experience with and understanding of deep neural networks and other machine learning techniques. Demonstrated ability to implement data science pipelines and real-time applications in Python 3+ years of relevant experience as a Data Engineer or similar roles. Proficiency with python-based tools like Jupyter notebook, coding standards like pep8. Experience with LLM/AI for data processing is a plus Exceptional analytical problem-solving abilities, with a strong attention to detail. Good command of English Excellent software development skills: ability to convert rough overall use-cases to a working codebase.\ Motivated by a deep curiosity and passion to learn is a plus. Past experience as a data scientist or data engineer in finance or investment profile is a plus. Experience with Linux/Unix shell and Git is a plus. What We Offer: Competitive and attractive compensation package with clear career road-map – where you feel challenged everyday We offer a strong culture of learning and development: training courses, library, speakers, share and learn events Learn from who sits next to you! Working in WQ you are surrounded by smart and talented people Premium Health Insurance and Employee Assistance Program Generous time-off policy, re-creation sabbatical leave (based on tenure), Trade Union benefits for staff and family Team building activities every month: Local engagement events, Employee clubs: football, ping-pong, badminton, yoga, running, PS5, movies, etc. Annual company trip and occasional global conferences – opportunity to travel and connect with our global teams Happy-hour with tea break, snacks and meals every day in the office! #LI-NV1 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.

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: WorldQuant is seeking an exceptional individual to join the firm as a Data Sourcing Specialist, with a focus on broker and alternative data. We aim to remain at the forefront of data discovery and utilization, and this person will be key to achieving that goal. The ideal candidate will identify and source new datasets by building and maintaining relationships with sell-side banks and data providers, attending industry events and conferences, and conducting in-depth research across data exchanges, industry publications, and sell-side materials. The successful candidate will partner closely with researchers and portfolio managers to understand their data needs and requirements, and will work cross-functionally with data providers, legal, compliance, data engineering and research management to support the full data lifecycle, including procurement, onboarding, renewals and decommissions. A compelling candidate will also have a strong background in data strategy, including assessing the data landscape, identifying the most attractive opportunities for the firm, and developing both short- and long-term plans to capture them. Finally, this person will also help improve our data operating model by identifying creative ways to apply new data across the firm and by automating data workflows using AI-based approaches. What You’ll Bring: Undergraduate degree in economics, finance, or a business-related discipline from a leading university 5+ years of relevant experience working with data providers; exposure to sell-side data is a plus Strong knowledge of financial instruments, industry terminology, and the quantitative investment process Demonstrated experience negotiating contracts and commercial terms, especially data licensing agreements Working knowledge of basic statistics and data science, and familiarity with AI and LLM applications Strong written and verbal communication skills, with excellent attention to detail and organizational discipline Ability to build effective relationships with senior stakeholders across investment, data engineering, legal, compliance, and related teams Maturity, sound judgment, and personal accountability, with a collaborative and team-oriented approach Genuine interest in using data to inform strategy and create business value Fluency in Japanese and/or Korean is plus, but not required #LI-RS1 WorldQuant is a total compensation organization where you will be eligible for a base salary, discretionary performance bonus, and benefits. The estimated salary range for this position is $125,000 to $175,000 which is specific to New York and may change in the future. When finalizing an offer we will take into consideration an individual’s experience level and the qualifications they bring to the role to formulate a competitive total compensation package. Position based in New York, NY or Old Greenwich, CTBy 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.

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Hyderabad, Telangana, India; Bengaluru, Karnataka, India.Minimum qualifications: Bachelor's degree in Engineering, Math, Quantitative Science, or a related technical field, or equivalent practical experience. 6 years of experience in conducting industry trend analysis and translating data into business insights in a data-driven corporate environment. Experience in writing SQL, analyzing data sets, building data pipelines, and design reporting dashboards. Preferred qualifications: Master's degree in a quantitative field (e.g., Statistics, Computer Science, Engineering, Mathematics, Data Science, etc.). 5 years of experience with designing experiments, developing statistical models, measurement, and identifying business opportunities. Experience in data analysis, with the ability to solve problems in complex, fast-moving, and ambiguous business environments reliable data intuition and business acumen. Experience influencing senior leadership on analytical decision making. Knowledge of Google tools (e.g., Plex). Ability to effectively communicate analysis and recommendations across a wide range of non-technical audiences. About the jobGoogle's leadership team hand-picks thorny business challenges, and members of BizOps work in small teams to find solutions. As part of this team you fully immerse yourself in data collection, draw insight from analysis, and then zoom out to develop compelling, synthesized recommendations. Taking strategy one step further, you also persuasively communicate your recommendations to senior-level executives, roll-up your sleeves to help drive implementation and check back-in to see the impact of your recommendations. As a Business Analysis Generalist, you are responsible to critically evaluate and synthesize analytical findings, then contextualize them against the relevant business objective or project question, drawing meaningful, justified conclusions and acknowledging data limitations to drive evidence-based decision-making. You will be required to work hours aligned with the North American time zone.Responsibilities Drive outcomes for one or more complex business analyses or overarching strategic pieces as an individual contributor. Lead efforts to translate data into insights, identify key market drivers, and design experimental frameworks using analytical tools to test hypotheses and draw conclusions. Design, architect, and deploy data strategies for reporting, data pipelines, and interactive dashboards. Partner with stakeholders to define success metrics and ensure repeatable analyses that optimize global vendor operations. Understand business requirements and processes and apply them to a solution design that meets user, quality, and sustainability requirements. Articulate and address conflicts between the goals and objectives of stakeholders by understanding the nature of the problem and its underlying assumptions. Communicate business results, related findings, and strategic roadblocks clearly to senior leadership and the broader organization by delivering high-impact presentations. 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.