Tìm kiếm việc làm online mới nhất!

建構與優化機器學習模型: 運用多維度運動數據（如賽事數據、球員表現），開發球員薪資計算、表現預測等核心模型，並持續進行優化。 支援產品與行銷決策: 深入分析用戶行為與市場趨勢，提供數據洞察，協助產品團隊優化功能、支援行銷團隊制定精準策略。 整合生成式 AI 應用: 導入並開發生成式 AI 功能，例如自動化產出運動新聞與球員動態，豐富產品內容。 提升內部數據工作流程效率: 運用 AI 技術優化資料處理、分析與建模的流程，提升團隊整體開發效率。

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. 2 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL) (or 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. 3 years of work experience with analysis applications (extracting insights, performing statistical analysis, or solving business problems), and coding (Python, R, SQL). 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.Responsibilities Execute defined, moderately difficult investigative tasks under guidance from the manager or executive team member/TL. Execute end-to-end analysis with minimal guidance. Manage workload to reflect the priorities set by the team, work towards a timeline, and communicate slippage. Handle data communication, limits, and importance. Collaborate with Product Managers, Engineers, and Research Scientists to define and track key performance indicators (KPIs) for Google Ads measurement products. Select appropriate approaches from clear options to address technical challenges under guidance from managers or executive team members.  Conduct in-depth analysis of large datasets to identify trends, patterns, and insights that inform product strategy and development. Communicate 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.

Responsibilities Lead the design and development of end-to-end data science projects, from business problem understanding to model deployment and monitoring.Collaborate with domain experts and cross-functional teams to translate business goals into goal-driven autonomous agent workflows.Design and implement robust RAG (Retrieval-Augmented Generation) pipelines to enhance the performance of large language model (LLM) applications.Prototype and deploy multi-agent LLM systems for planning, reasoning, and task orchestration. Build and deploy machine learning models for use cases such as recommendation systems, NLP, time-series forecasting, and computer vision.

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, Machine Learning, Data Science, Economics, or a related quantitative field. Experience with developing machine learning models, launch experiments (e.g., A/B Testing), and end-to-end data infrastructure and analytics pipelines. Experience in developing new models, methods, analysis and approaches. Experience with classification and regression, prediction and inferential tasks, training/validation criteria for Machine Learning (ML) algorithm performance. Experience in identifying opportunities for business/product improvement and defining the success of initiatives. Ability to manage problems, with excellent communication and presentation skills to deliver findings of analysis. About the jobIn this role, you will partner with Product Manager (PM), engineer, User Experience (UX) and cross-functional teams to shape the product narrative and build or launch features.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 Perform analysis utilizing related tools (e.g., SQL, R, Python). Help solve problems, narrow down multiple options into the best approach, and take ownership of open-ended business problems to reach a solution. Build new processes, procedures, methods, tests, and components to anticipate and address future issues. Report on Key Performance Indicators (KPIs) to support business reviews with the cross-functional/organizational leadership team. Translate analysis results in business insights or product improvement opportunities. Build and prototype analysis and business cases to provide insights. Develop knowledge of Google data structures and metrics. Advocate for changes needed for product development. 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.

Logitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.The RoleLogitech is the Sweet Spot for people who want their actions to have a positive global impact while having the flexibility to do it in their own way.We are seeking a highly skilled Senior Data Scientist to join the Digital Growth Solutions organization. In this role, you will leverage your analytical skills, machine learning knowledge, and Gen AI-proficiency to uncover insights from commercial and customer service data.You will act as a technical bridge, supporting our Marketing Data Hub Product Owner and Segmentation Leads to drive data-informed decision-making across campaigns and digital experiences. This role blends immediate execution on our Customer Data Platform (CDP) with a strategic 12-18 month roadmap to build our internal Marketing Mix Modeling (MMM) capability.Your ContributionBe Yourself. Be Open. Stay Hungry and Humble. Collaborate. Challenge. Decide and just Do. These are the behaviors you’ll need for success at Logitech. In this role, you will:1. Advanced Analytics Machine LearningPredictive Modeling: Build, evaluate, and deploy predictive models using Python to solve real-world problems (e.g., churn prediction, LTV forecasting, and propensity scoring).Explainable AI: champion Explainable ML (e.g., SHAP values) to ensure non-technical stakeholders understand why a model is making specific recommendations.Generative AI: Integrate GenAI tools into data workflows to enhance productivity and generate insights from unstructured text (e.g., customer service logs).2. CDP Strategic CollaborationMarketing Data Hub: Support the Product Owner by designing analytic solutions that support specific business initiatives, ensuring our data strategy aligns with commercial goals.Segmentation Strategy: Partner with Segmentation Leads to perform targeted analysis, identifying meaningful customer patterns to refine our audience strategy.Actionable Insights: Translate complex findings into compelling stories via Tableau dashboards and visualizations that drive business action.3. Engineering Data FoundationsData Quality Pipelines: Evaluate data quality and propose cleaning strategies. Work with structured and unstructured data, designing efficient pipelines (using AWS Lambda, Athena) to ensure reliable data.Reproducibility: Develop reproducible data science workflows (not just ad-hoc scripts) in Jupyter Notebooks and productionize them via Snowflake.Marketing Mix Modeling (MMM): Over time, architect the end-to-end development of Logitech’s in-house MMM framework to measure ROI across online and offline channels.Key QualificationsFor this role, we need a blend of an Engineer’s discipline and a Statistician’s mind.Education Experience:Bachelor’s or Master’s degree in Computer Science, Statistics, Engineering, or a related field.8 years of experience in a Data Science role, specifically with a focus on marketing, customer analytics, or commercial data.Core Stack: Strong proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL (Snowflake required).Cloud Architecture: Hands-on experience with AWS Cloud Services is a strong plus (SageMaker, S3, Athena, Lambda).Statistical Depth: Solid understanding of regression analysis, classification, time-series forecasting, and experimental design (A/B testing).Visualization: Experience with Tableau or similar BI tools for dashboarding.Business Acumen: Advanced proficiency in designing analytic solutions based on vague business requirements.Communication: Strong skills to present and engage with non-technical stakeholders (Marketing Directors, Finance partners).Autonomy: Ability to work independently in a fast-paced, matrixed environment.Curiosity: A Hungry and Humble attitude—willing to learn new stacks (like GenAI) and challenge the status quo.Across Logitech we empower collaboration and foster play. We help teams collaborate/learn from anywhere, without compromising on productivity or continuity so it should be no surprise that most of our jobs are open to work from home from most locations. Our hybrid work model allows some employees to work remotely while others work on-premises. Within this structure, you may have teams or departments split between working remotely and working in-house.Logitech is an amazing place to work because it is full of authentic people who are inclusive by nature as well as by design. Being a global company, we value our diversity and celebrate all our differences. Don’t meet every single requirement? Not a problem. If you feel you are the right candidate for the opportunity, we strongly recommend that you apply. We want to meet you!We offer comprehensive and competitive benefits packages and working environments that are designed to be flexible and help you to care for yourself and your loved ones, now and in the future. We believe that good health means more than getting medical care when you need it. Logitech supports a culture that encourages individuals to achieve good physical, financial, emotional, intellectual and social wellbeing so we all can create, achieve and enjoy more and support our families. We can’t wait to tell you more about them being that there are too many to list here and they vary based on location.All qualified applicants will receive consideration for employment without regard to race, sex, age, color, religion, sexual orientation, gender identity, national origin, protected veteran status, or on the basis of disability.If you require an accommodation to complete any part of the application process, are limited in the ability, are unable to access or use this online application process and need an alternative method for applying, you may contact us toll free at 1-510-713-4866 for assistance and we will get back to you as soon as possible.

Minimum qualifications: Master's degree in Statistics, Data Science, Mathematics, Physics, Economics, Operations Research, Engineering, or a related quantitative field or equivalent practical experience. 5 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 3 years of experience with a PhD degree. Preferred qualifications: 8 years of experience using analytics to solve product or business problems, coding (e.g., Python, R, SQL), querying databases or statistical analysis, or 6 years of experience with a PhD degree. Experience with data, metrics, analysis and trends with the knowledge of measurement, statistics and program evaluation. Ability to learn about Supply Chain Operations. Excellent problem-solving and business judgment skills. About the jobThe Cloud Supply Chain Data (CSCD) Data Science and Product team build productivity and data products, develop Artificial Intelligence (AI)/Machine Learning (ML)/statistical models and provide insights to help Cloud Supply Chain and Operations (CSCO) define and achieve business goals.The AI and Infrastructure team is redefining what’s possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.We're the driving force behind Google's groundbreaking innovations, empowering the development of our cutting-edge AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.Responsibilities Develop machine learning and statistical models to detect anomalies, forecast trends, classify patterns and optimize processes in Google Cloud Supply Chain and Operations. Deliver investigative problems with guidance structuring approach and conduct exploratory data analysis, inform model design, and development. Plan and execute prioritized project work, including selecting appropriate methods and advising on opportunities to improve data infrastructure. Identify and recommend ways to improve solutions to problems by selecting better methods or tools. Identify issues with scope, data, or approach. Escalate issues to be addressed by stakeholders and communicate, present insights, and recommend actions to 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: 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. Experience with Google Ads products and technologies. Familiarity with privacy-preserving technologies and data regulations (e.g., GDPR, CCPA). Knowledge of machine learning techniques and their applications in advertising. Understanding of digital advertising measurement concepts, including attribution modeling, incrementality testing, and Media Mix Modeling (MMM). 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 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. Collaborate with Product Managers, Engineers, and Research Scientists to define and track key performance indicators (KPIs) for Google Ads measurement products.  Communicate complex data and analysis in a clear and concise manner to various stakeholders, including product leadership, engineering teams, and business partners. Conduct in-depth analysis of large datasets to identify trends, patterns, and insights that inform product strategy and 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: 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.

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.