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為什麼大家喜歡在 RichWell Co.Ltd. 上班? 1.彈性上班-早上不趕打卡,想多睡一點、避開通勤人潮都OK。2.特休多多-不用等滿一年就能休假,我們比法規更大方,放假就是要爽爽的。3.獎金福利讚 年終、績效獎金該有的都有,努力絕對不白費。4.生日小驚喜,公司記得你的每個重要時刻。5.定期聚餐/Team Building 不只是工作夥伴,更是一起成長的戰友,吃吃喝喝感情更緊密。6.技術課、內部分享會,想學什麼我們都支持,讓你持續進化不退化! Key Responsibilities for Data Analyst: Responsible for gathering data from various sources, including internal databases, user interactions third-party APIs, ensuring data accuracy and integrity.Perform exploratory and statistical analysis to identify trends, patterns, and correlations in large datasets.Create clear, compelling reports and dashboards to communicate insights of the product to stakeholders.Work closely with product and engineering teams to define key performance indicators (KPIs) and track product performance.Provide recommendations to improve software features, user engagement, and operational efficiency based on data findings.Implement processes to ensure data quality, consistency, and security, adhering to company policies and regulations.Conduct custom analyses to support strategic initiatives or respond to business questions.
115K ~ 127K TWD / month
2 years of experience required
No management responsibility
At SWAG Live's data team, our mission is to democratize data by building a self-service data platform. We aim to empower internal teams to access, interpret, and derive valuable insights from data effectively.As a Data Scientist in this role, you will collaborate with a multidisciplinary team of engineers and analysts to tackle diverse challenges using quantitative techniques such as statistical analysis and machine learning. You will work with large, complex event-based datasets, conduct exploratory data analysis (EDA), define requirements, and develop deploy models. We are particularly seeking a data scientist with experience in building customized recommendation models and a strong interest in product-focused machine learning development. Responsibilities Leverage state-of-the-art algorithms to build fully customized recommenders and other growth models.Design, deploy and maintain all components necessary for modeling, including feature engineering, automatic model training tuning and engineering toolchains.Create a comprehensive monitoring framework to evaluate model performance and provide actionable insights to drive business growth, focusing on awareness conversion and transactions.Understand stakeholder business requirements and design end-to-end machine learning/AI solutions that are effective, practical, and robust in addressing business challenges.Collaborate closely with data engineers and backend engineers to develop scalable systems.Communicate efficiently with cross-functional teams, promote the implementation of strategic applications, and drive continuous optimization.
Negotiable
3 years of experience required
No management responsibility
DescriptionAt SWAG Live, data is the backbone of how we innovate and grow. With our BI system established, the data team is now focused on building the next generation of platforms that power recommendation systems, AI agents, AI pipelines, and campaign-facing services—as well as external-facing data services that enhance our products. We are seeking a Data Engineer who will design and operate the infrastructure that makes these AI-driven initiatives possible. Your work will center on building cost-efficient, reliable, and maintainable systems that deliver measurable business value. You’ll collaborate closely with data scientists and product teams to turn models into production-ready services, enabling personalization, campaign optimization, and intelligent product features. This is a role for engineers who want to shape the future of applied AI while keeping efficiency at the core. Responsibilities Build and maintain cost-efficient data pipelines and warehouses that power analytical tool, recommendation systems, AI agents, and campaign-facing services.Develop data services that integrate with external products, ensuring reliability, maintainability, and clear SLAs.Optimize queries, schemas, and storage to maximize performance and minimize cost across transactional and analytical workloads.Implement and operate event-driven streaming architectures for real-time personalization and campaign insights.Collaborate with data scientists and product teams to move AI models from experimentation to production.Create internal tools and frameworks that accelerate the productivity of analysts, scientists, and engineers.Ensure data quality, governance, and observability across pipelines and services.
Negotiable
3 years of experience required
No management responsibility
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.
Negotiable
No requirement for relevant working experience
About BTSE:彼特思方舟 is a specialized service provider dedicated to delivering a full spectrum of front-office and back-office support solutions, each of which are tailored to the unique needs of global financial technology firms. 彼特思方舟 is engaged by BTSE Group to offer several key positions, enabling the delivery of cutting-edge technology and tailored solutions that meet the evolving demands of the fintech industry in a competitive global market.About the Role:We are seeking a dynamic and strategic Data Product Manager to bridge the gap between product innovation and data-driven insights. This role is responsible for defining and executing a data strategy that enhances our product offerings, optimizes decision-making, and drives business growth. You will work closely with cross-functional teams—including product, engineering, data science, and analytics—to ensure that data is at the heart of our product strategy and execution.Responsibilities:Understand product values and feature details to translate them into precise data requirements.Prioritize the product-related data requests backlog to align with product strategic objectives.Address gaps in our data ecosystem by defining tracking specifications and ensuring successful implementation and launch.Comprehend the meaning of data and clearly explain its context and significance to the data team for effective analysis.Initiate data insight projects with the data team for internal sharing and continuous product improvement.Qualifications:3+ years of experiencein data, analytics, or a related roleExperience definingdata tracking / event specsand coordinating with engineering or data teamsComfortable definingdata requirements, and able to structure dashboards and metrics based on product or business needsFamiliar withtrading products and workflows(e.g. stocks, futures, or crypto), with enough hands-on exposure to understand user behavior and data needsAble tocommunicate clearlywith product, engineering, and data teamsBonus Points:Experience in the blockchain or financial technology industry.Background in data analysis or data science.Perks Benefits:Competitive salary and benefits package.Opportunity to work in a fast-paced and innovative environment.Be part of a growing and dynamic team.Make a real impact on the company's success.Various team building programs and company events.Comprehensive healthcare schemes for employees and dependants.And many more! Apply and let us tell you more!#LI-JY1
Negotiable
No requirement for relevant working experience
Google will be prioritizing applicants who have valid working rights in Thailand and do not require Google’s sponsorship of a visa.Minimum qualifications: Experience with assembly of mechanical or electrical systems, or performing component-level repairs and troubleshooting on technical equipment. Experience with diagnosing and troubleshooting operating systems, computer hardware and server hardware. Experience with networking protocols. Ability to lift/move 50lb (23kg) of equipment and ability to exert yourself physically over extended periods of time, including frequent bending, kneeling, climbing, pushing/pulling and lifting. Ability to work non-standard hours, including working weekends, night shifts, holidays and on shift-based schedules as required. Preferred qualifications: Bachelor's degree or equivalent practical experience. 4 years of experience in maintenance and monitoring of server systems. Experience with performing component-level repairs and troubleshooting on IT equipment or in a related role (e.g., Systems Administration, Network Deployment Engineer, Help Desk Technician, etc). Experience working within a data center or network operation center environment. Experience with Linux operating systems. Experience in project management and leadership, and collaborating and partnering with teams. About the jobGoogle isn't just a software company. The Hardware Operations team is responsible for monitoring the physical infrastructure behind Google's powerful search technology. As an Operations Technician, you'll install, configure, test, troubleshoot and maintain hardware (like servers and its components) and server software (like Google's Linux cluster). You'll also take on the configuration of more complex components such as networks, routers, hubs, bridges, switches and networking protocols. You'll participate in or lead small project teams on larger installations and develop project contingency plans. A typical day involves manual movement and installation of racks, and while it can sometimes be physically demanding, you are excited to work with infrastructure that is at the cutting-edge of computer technology.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 team 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 Deploy and operate new data center infrastructure across teams. Report issues and follow data center procedures to troubleshoot and diagnose somewhat issues with equipment or infrastructure as they arise, and applying the resources needed to resolve identified issues. Maintain the security and integrity of data, track various forms of media to check for non-standard data security issues (e.g., data was not properly erased) handled in accordance with Google security standards. Disassemble specific equipment that has reached its end-of-life via part replacement or maintenance, within one or more teams. Repair, fix, and perform preventative maintenance on equipment, servers, machines, or infrastructure based on identified issues with multiple solutions, separately. 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.
Negotiable
No requirement for relevant working experience
職務內容(Responsibilities) 分析行銷與銷售數據,包含廣告成效、會員行為、轉換率、回購率等 對虛擬客服對話資料做文字/語意分析,提取客戶問題類型、反饋趨勢與滿意度指標 分析實體商店的人流量變化與顧客行為(進店/停留時間/熱點區/動線分析) 建立與維護 Dashboard,以視覺化方式呈現 KPI、行銷 ROI、客戶分類等指標 與行銷/業務/操作團隊合作,提出優化建議並參與 A/B 測試或活動效果評估 (加分)串接 CRM 或客戶資料庫以做個人化推播或忠誠顧客辨識 條件要求(Requirements) 擅長使用 Excel / SQL / Python 或 R 分析工具 熟悉資料視覺化工具,如 Tableau、Power BI 或類似儀表板工具 有行銷或業務數據分析經驗者佳,尤其有做過客戶對話分析或實體人流分析者更佳 能撰寫簡報給管理層/非技術人員,清晰傳達分析結果與建議 工作態度主動,對數據敏感,有邏輯思考能力 待遇與條件 全職/兼職/實習皆可(視需求) 薪資範圍根據經驗與能力而定 工作地點:可遠端 / 台北市 /與公司協商 加分條件:熟悉 NLP /語意分析、熟悉客流偵測技術、有人流計算或熱點分析經驗
700 ~ 1K TWD / hour
3 years of experience required
No management responsibility
Minimum qualifications: Bachelor's degree in Statistics, Mathematics, Data Science, Engineering, Physics, Economics, or a related quantitative field. 10 years of experience using analytics to solve product or business problems, performing statistical analysis, and coding (e.g., Python, R, SQL) or 8 years of experience with a Master's degree. Preferred qualifications: Experience with developing at least one deep learning or conventional machine learning model for business impact. Experience debugging throughput, latency and response quality issues in AI products, from an analytical perspective. Experience managing large-scale data transformation pipelines for batch inference of ML models. About the jobHelp serve Google's worldwide user base of more than a billion people. Data Scientists provide quantitative support, market understanding and a strategic perspective to our partners throughout the organization. As a data-loving member of the team, you serve as an analytics expert for your partners, using numbers to help them make better decisions. You will weave stories with meaningful insight from data. You'll make critical recommendations for your fellow Googlers in Engineering and Product Management. You relish tallying up the numbers one minute and communicating your findings to a team leader the next. The Googler Technology and Engineering (GTE) team partners with teams across the company to apply Google’s best Data Science techniques to Google’s biggest enterprise opportunities. We partner with Research, Core Enterprise Machine Learning (ML) and ML Infrastructure teams to build solutions for our enterprise.The GTE Data Science team's mission is to:Transform Google Enterprise business operations, supply chain, IT support and internal tooling with AI and Advanced AnalyticsEnable operations and product teams to succeed in their advanced analytics projects through the use of differing engagement models, ranging from consulting to productionizing and deploying modelsBuild cross-functional services for use across Corporate EngineeringEducate product teams on advanced analytics and MLResponsibilities Define and report key performance indicators and launch impact as part of regular business reviews with the cross-functional and cross-organizational leadership team. Translate analysis results to business insights or product improvement opportunities.  Develop hypothesis to enhance performance of AI products on offline and online metrics through research on techniques around prompt engineering, RAG, supervised finetuning, in-context learning, dataset augmentation, tool-calling efficacy, planning capabilities and feedback loop with reinforcement learning. Design and develop ML strategies for data enrichment such as autoencoder based latent variables, complex heuristics etc. Evolve variance reduction and simulation strategies to increase reliability of experiments with small sample sizes. Unlock continually improving experimentation with algorithms like contextual bandits.  Convert business problems into unsupervised and supervised machine learning modeling problems, and build these model prototypes from scratch to justify business impact hypothesis. 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.
Negotiable
No requirement for relevant working experience
Google will be prioritizing applicants who have a current right to work in Singapore, and do not require Google's sponsorship of a visa.Minimum qualifications: Bachelor's degree in Mechanical Engineering, Electrical Engineering or IT Engineering, or equivalent practical experience. 5 years of experience working with external telecom vendors on telecom products. Preferred qualifications: Master's degree in Mechanical or Electrical or IT engineering. 6 years of experience as a Registered Communications Distribution Designer (RCDD) Certified professional with ICT/telecom scope within mechanical and electrical data center products. 6 years of experience as key contributor on ICT/telecom scope within mechanical and electrical data center products Experience with Autodesk Revit or other 3D modeling software developing telecom rack and tray layouts. Ability to travel to visit data center sites or manufacturing partners. About the jobOur thirst for technology is a part of everything we do. The Data Center Engineering team takes the physical design of our data centers into the future. Our lab mirrors a research and development department -- cutting-edge strategies are born, tested and tested again. Along with a team of great minds, you take on complex topics like how we use power or how to run state-of-the-art, environmentally-friendly facilities. You're a visionary who optimizes for efficiencies and never stops seeking improvements -- even small changes that can make a huge impact. You generate ideas, communicate recommendations to senior-level executives and drive implementation alongside facilities technicians. The Data Center Design Integration team is a multi disciplinary team of architects and Information and Communication Technology (ICT)/Telecommunications (Telecom) designers that work on next generation data center designs. We are a sub-team of the broader Data Center Technology and Systems (DCTS) organization.As a Telecom Lead, you will be responsible for working with executive level engineers across all disciplines to develop integrated telecom communication designs at the product and top level assembly state of a data center. You will lead external consultants to develop coordinated construction level drawing packages for manufacturing and construction.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 team 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 Work with internal telecom engineers and network designers to rationalize requirements into products, conceptual one lines and conceptual rack or tray layouts to enable adequate telecom infrastructure. Work with cross-functional disciplines across architecture, civil, mechanical, electrical, controls, security on product development, and assembly integration of telecom infrastructure. Participate in internal and external ICT/telecom product and data center design reviews across the following disciplines: Telecom, Security, Controls and Networking. Review construction level drawings produced by internal and external vendors that document ICT/telecom scope for program reference. Review and enable best practices for converged network allocations across all mechanical, electrical, and controls products. Act as an escalation path for site localization of canonical design where local requirements necessitate engineering judgement on adjustments to ICT/telecom design. 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.
Negotiable
No requirement for relevant working experience
At MoMo, we are not just processing transactions; we are shaping the future of finance in Vietnam.You will work with experienced data professionals, explore how analytics supports real business decisions, and gradually gain hands-on experience in building data products—from raw data to insights and reusable data assets—used across MoMo’s products and internal platforms.Mô tả công việcLearn and work with semantic / metrics layers (e.g. semantic models, metrics definitions, dimensions) to support consistency across dashboards and analyses.Build and maintain automated dashboards to monitor key performance metrics, with guidance from the team.Analyze datasets to generate insights that support business and product decision making.Develop an understanding of the “Data as a Product” mindset, contributing to data solutions that are reliable, well-documented, and reusable.Gain hands-on experience with workflow orchestration tools such as Airflow, n8n, or similar platforms.Collaborate with internal teams to understand business needs and support the delivery of data solutions.Support cross-functional projects by contributing analytical insights and data foundations.Yêu cầu công việcUniversity degree (BA, BSc, etc.) in a quantitative discipline or with quantitative/statistics coursework such as Statistics, Computer Science, Mathematics, Information Management, Business, Economics, Marketing, or relevant.Strong analytical mindset to support data-driven decision making.Fast learner with high learning agility, eager to pick up new data tools and concepts.Data product mindset: build reliable, reusable datasets beyond one-off reports.Proficiency in SQL and comfort working with large datasets.Clear communication skills (English Vietnamese) and ability to collaborate cross-functionally.
No requirement for relevant working experience

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