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At MoMo, we are not just processing transactions; we are shaping the future of finance in Vietnam.As a Data Analyst Trainee in the Corporate Data Office (CDO), this role is an opportunity for you to learn by doing.You will be guided by 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 việcFinal-year student or fresh graduate in Data, Computer Science, Statistics, Economics, or related fieldsStrong analytical mindset to support data-driven decision makingFast learner with high learning agility, eager to pick up new data tools and conceptsData product mindset: build reliable, reusable datasets beyond one-off reportsBasic proficiency in SQL and comfort working with large datasetsClear communication skills (English Vietnamese) and ability to collaborate cross-functionally

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.

The MoMo Recommendation Platform is a complex system that powers personalized experiences for millions of users using a diverse range of technologies.We’re looking for a Senior Software Engineer with strong system thinking, architecture design skills, and a product mindset to help build the MLOps platform that transforms any AI/ML solutions into production-grade systems at scale.Mô tả công việcThink like a product engineer: you don’t just “code a solution” – you build a platform that empowers others to deliver intelligent sysDesign and develop a flexible platform that turns AI/ML solutions into production-ready systems: microservices, batch pipelines, or real-time APIsBuild infrastructure to support:Model training pipelinesPackaging deploymentServing rolloutMonitoring alertingCollaborate closely with Data Scientists, Business, and Product teams to deeply understand requirements and design adaptable, scalable solutionsIntegrate platform components into MoMo’s broader infrastructure: promotion engine, A/B testing, analytics, real-time scoring, etc.Yêu cầu công việcMust-Have5+ years of experience in software development, system architecture, or backend/platform engineeringProficiency in one or more of the following: Python, Bash, C++, JavaScript, Java, or GoStrong problem-solving skills and teamwork spiritExperience with:Platform Deployment: Kubernetes, Helm, Argo CD, Argo Rollouts, Docker, Google Cloud Platform (GCP) or Amazon Web Services (AWS)Serving APIs: FastAPI, gRPC, MLflow, KServe, custom logic services, REST APIsData Messaging: BigQuery, Redis, MongoDB, PostgreSQL, Oracle, MySQL, Kafka, Pub/SubOrchestration Workflow: Airflow, Argo WorkflowsCI/CD Monitoring: GitHub Actions, Prometheus, GrafanaData Sources: App event streams, relational databases, messaging systems, APIsSolid understanding of distributed systems and cloud-native architectureAbility to design systems that support diverse solution typesPlatform mindset: you build for stability, scalability, and long-term maintainabilityStrong communication and collaboration skills – able to work cross-functionally with Data Scientists, DevOps, and Product teamsNice-to-HaveExperience working with both AI/MLExperience scaling low-latency / real-time systemsFamiliarity with A/B testing, canary release, and shadow deployment strategiesProduct-oriented mindset: you build systems that others can easily adopt and extend

Google welcomes people with disabilities.Minimum qualifications: Bachelor’s degree or equivalent practical experience. 2 years of experience in program management. 2 years of experience designing, constructing, or managing infrastructure projects. Experience creating infrastructure designs (e.g., telecom, electrical, mechanical), drawing sets for builds, and remodels of data center networking spaces. Preferred qualifications: Bachelor's degree in Electrical Engineering, Mechanical Engineering, or Computer Science or equivalent practical experience. 5 years of experience with technical program management. Experience with two or more of the following: data center design, network hardware and software, data center infrastructure and operations or mechanical and electrical systems. Experience managing programs through the entire program management cycle. Experience with AutoCAD. Excellent problem-solving and quantitative skills, with the ability to report out on process improvements, issues, and program highlights. About the jobThe 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 Design and optimize the physical layout of data center floors, ensuring efficient use of space and resources. This includes placement of server racks, network equipment, power distribution units (PDUs), and cooling systems. Design cable tray systems to support data and power cabling for server racks and other equipment.  Calculate power requirements for server racks and other equipment, taking into account redundancy and future growth. Collaborate with electrical engineers to design power distribution systems. Determine optimal placement and configuration of server racks, ensuring adequate airflow, bus duct accessibility, optimal network cable routes and maintenance accessibility. Develop detailed 2D and 3D drawings using Computer-Aided Design (CAD) and Building Information Modeling (BIM) software. Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

Minimum qualifications: Bachelor's degree in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience. 3 years of experience with interactions between hardware and software at the system level. Preferred qualifications: Master's degree or PhD in Computer Science, Electrical Engineering, a related technical field, or equivalent practical experience. Experience with liquid cooling technologies (e.g., DLC, sidecars) and their application in data center environments. Experience with server hardware from Dell (PowerEdge), HPE, and NVIDIA (HGX/NVL platforms). Experience with thermal modeling or Computational Fluid Dynamics (CFD) software to predict hotspot formation in high-density racks. Familiarity with high-power electrical standards and facility interfaces for liquid-cooled hardware. About the jobThe Google Cloud team helps companies, schools, and government seamlessly make the switch to Google products and supports them along the way. You listen to the customer and swiftly problem-solve technical issues to show how our products can make businesses more productive, collaborative, and innovative. You work closely with a cross-functional team of web developers and systems administrators, not to mention a variety of both regional and international customers. Your relationships with customers are crucial in helping Google grow its Cloud business and helping companies around the world innovate. Google is bringing our cloud anywhere with Google Distributed Cloud—in your data center, at the edge, and in the cloud.Google Distributed Cloud (GDC) is a portfolio of fully managed Hardware (HW) and Software (SW) solutions which extends Google Cloud’s infrastructure to the edge and to customers’ data centers. It is enabled by Anthos and is ideal for local data processing, edge-computing for latency-sensitive workloads, and for meeting sovereignty, strict data security, and privacy requirements.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.Responsibilities Lead mechanical, thermal, and power design and validation for GDC rack infrastructure, accommodating next-generation advanced GPUs, including platforms such as NVIDIA Blackwell, Rubin, and future high-density AI accelerators. Analyze power consumption and thermal output of new components (e.g., servers, ToRs, switches, HSM, etc.) to determine impact on the existing rack designs, specifically addressing the shift to liquid-cooled requirements. Work closely with Original Equipment Manufacturer (OEMs), Product and Engineering teams to analyze their specific Hyperscale Graphics eXtension (HGX). Calculate rack power budgets and density limits, ensuring designs accommodate high-voltage requirements without exceeding infrastructure capacity. Model and validate airflow for mixed environments, including the integration of liquid-to-air sidecar heat exchangers. 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.

Google welcomes people with disabilities.Minimum qualifications: Bachelor's degree or equivalent practical experience. 5 years of experience using Python (Pandas, NumPy) or Java to develop data processing tools or automation scripts. Experience in managing data workflows using tools like Airflow, dbt, or Prefect. Experience in building and querying data within BigQuery, Snowflake, or Redshift environments. Experience in developing operational dashboards using Looker, Tableau, or Power BI. Preferred qualifications: Experience working with semiconductor manufacturing data or large-scale industrial datasets. Ability to manage complex data exchanges and integration workflows with external foundry or assembly partners. Ability to identify manufacturing anomalies and to explain architectures to non-technical stakeholders. About the jobA problem isn’t truly solved until it’s solved for all. That’s why Googlers build products that help create opportunities for everyone, whether down the street or across the globe. As a Program Manager at Google, you’ll lead complex, multi-disciplinary projects from start to finish — working with stakeholders to plan requirements, manage project schedules, identify risks, and communicate clearly with cross-functional partners across the company. Your projects will often span offices, time zones, and hemispheres. It's your job to coordinate the players and keep them up to date on progress and deadlines. As a Machine Learning Data and Analytics Engineer, you will be the architect of manufacturing intelligence. You will design, build, and maintain the data infrastructure that transforms fragmented information from the global partners into a cohesive, high-performance data ecosystem. Your work will directly enable the operations team to monitor production health, optimize yields, and make data-driven decisions in real-time.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 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 Design and deploy pipelines to manage high-volume manufacturing data, including wafer maps, test results, and quality reports. Build automated tools to clean and normalize disparate data formats from foundry and assembly partners, ensuring a single source of truth. Create and maintain intuitive visualizations and dashboards to monitor the Key Performance Indicator (KPIs) and production health metrics. Develop and optimize data schemas that support high-speed ingestion and investigative querying for real-time decision-making. Partner with Operations and Engineering teams to translate business requirements into technical solutions while ensuring platform reliability and performance. 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.Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. The Role: As an NLP Data Engineer at WorldQuant, you will be at the heart of transforming unstructured text into actionable, high‑value insights that power quantitative investment strategies. This is a hands-on, engineering role where you’ll design, build, and scale the data pipelines that underpin our data research. This role is ideal for someone who loves building production systems, enjoys working deeply with text and large language models, and wants their engineering work to empower quantitative research at the firm. You’ll join a highly technical, collaborative environment where you work closely with Research and where your ideas can quickly translate into impact at scale. What You’ll Bring: BSc/M.Sc. from a leading university in Computer Science, Engineering, or related discipline 5 years of demonstrated experience programming scalable and robust software in Python Demonstrated experience building or maintaining data pipelines Basic knowledge of probability and statistical theory Experience working in Linux environments Experience with building and operating ML inference pipelines. Experience with using LLM for structured data extraction. Strong communication skills; ability to express complex concepts in simple terms Experience in the financial services industry is a big plus Knowledge of workflow scheduling techniques (e.g. Airflow) is a plus Prior experience working with text data in a data science/quantitative project environment 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-QM1By 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.Technologists at WorldQuant research, design, code, test and deploy firmwide platforms and tooling while working collaboratively with researchers. Our environment is relaxed yet intellectually driven. We seek people who think in code and are motivated by being around like-minded people. The Role: We're seeking a senior developer to join our team. You will design, build, and operate large-scale data and ETL systems that power the firm's research and investment workflows. This is a high-autonomy role - you'll own critical systems end-to-end, make architectural decisions, and deliver solutions with minimal guidance. We need someone who is self-directed, able to lead themselves, take ownership of outcomes, and drive complex problems to resolution independently. You should be comfortable communicating across teams, articulating technical trade-offs to stakeholders, and mentoring others through code review and collaboration. What You'll Do: Design, develop, and own backend services and data pipelines that process large volumes of data optimally and at scale Architect data storage and processing solutions, including schema design, query optimization, and data modeling Build and maintain APIs, messaging systems, and integration layers that connect data producers and consumers Drive technical decisions - evaluate trade-offs, choose the right tools, and define system boundaries Take ambiguous requirements and break them down into deliverable, well-engineered solutions Diagnose and resolve complex production issues - applying strong analytical and systems thinking Improve engineering practices: testing, CI/CD, observability, and documentation What You'll Bring: 8+ years of professional software development experience Strong programming proficiency: Mastery of at least one major programming language (Python, Java, Go, C++, or equivalent). Beyond syntax fluency, you should understand language internals and be able to apply that depth to write performant, reliable code System design: Proven ability to architect distributed, scalable, and fault-tolerant systems. Understanding of common patterns - event-driven architecture, service decomposition, data partitioning, caching strategies Data engineering: Experience building ETL/ELT pipelines, working with batch and streaming data, and handling large-scale data processing Database proficiency: Deep understanding of relational databases (PostgreSQL, MySQL) and familiarity with analytical/columnar stores; strong SQL skills including query optimization Software engineering depth: Strong grasp of data structures, algorithms, design patterns, and software architecture principles - applied in production, not just theory API design: Experience designing clean, well-documented REST/gRPC APIs Incident response mindset: Ability to diagnose production issues methodically, drive root-cause analysis, and feed into post-mortems and operational improvement AI-agent readiness: Openness to working alongside AI coding agents and LLM-powered tools as part of the development workflow - using AI as a force multiplier for code generation, review, debugging, and documentation Nice to Have: Python mastery: Advanced knowledge of Python internals, concurrency (asyncio, threading, multiprocessing), performance profiling, packaging, and strong experience with frameworks such as FastAPI/Flask, SQLAlchemy, pytest, and mypy/type annotations Observability and distributed tracing: Experience with monitoring and observability stacks - metrics, structured logging, distributed tracing (OpenTelemetry, Grafana, ELK) - for diagnosing system behavior and bottlenecks in production DevOps practices: Familiarity with containerization (Docker), CI/CD pipelines (GitLab CI, Jenkins), and infrastructure-as-code (Ansible, Terraform) Programming language versatility: Proficiency in additional languages that complement data platform work - C++ for performance-critical systems, Scala for distributed data processing with Apache Spark, or Rust for high-performance data engineering Team leadership and management: Experience leading a development team, running sprints, conducting code reviews, mentoring engineers, and managing stakeholders' expectations Message queues and streaming: Experience with Kafka, Redis, or similar event-driven architectures Data orchestration: Exposure to Airflow or similar workflow orchestration frameworks Frontend / full-stack awareness: Familiarity with modern web technologies (React, TypeScript) for building internal UIs and dashboards Financial services or quantitative finance background Open-source contributions or a public portfolio of technical work 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-QM1 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.

公司介紹 我們的客戶是一家長期深耕金融科技與數位創新的大型金融機構，近年積極投入資料平台與雲端架構升級，打造企業級數據基礎設施，支援數據分析、AI模型與多元金融場景。 團隊目前正推動 Modern Data Stack 與資料治理體系建設，導入雲端數據平台、資料血緣管理與自動化資料流程，讓數據能真正驅動產品決策與金融服務創新。 對資料工程師而言，這是一個能接觸 大規模資料、成熟商業場景與完整數據治理架構 的環境，能在穩定產業背景下，參與企業級資料平台的設計與落地。 工作內容 設計與維護 雲地混合（Hybrid Cloud）數據架構 建立與開發 大規模 Data Pipeline，處理結構化、半結構化與非結構化資料 建立資料處理流程的 自動化監控與維運機制 評估與導入 Modern Data Stack，提升資料治理、品質與血緣管理能力 使用資料治理與元資料管理工具，管理企業數據資產 維護與優化 Airflow 工作流程平台，支援資料科學與分析團隊的資料處理流程 設計部署與監控策略，確保資料平台穩定與高可用性 使用的技術 Python SQL Apache Airflow GCP（Composer / Dataflow） Terraform CI/CD Pipeline Data Governance / Data Lineage Modern Data Stack

・與產品、風控、運營團隊協作，針對業務需求定義資料模型與監控指標・建置 ETL 流程，收集與清洗來自平台的行為數據（如下注記錄、轉碼、點擊行為）・開發與維護異常偵測模型（如洗碼對打、機器人行為、套利用戶）・利用機器學習或統計模型預測玩家留存、LTV、流失風險・設計風控策略，提升平台資金與行爲風險控制能力・定期產出分析報告，提出可行的產品或營運優化建議