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At MoMo, we are not just processing transactions; we are shaping the future of finance in Vietnam. We are seeking a visionaryAnalytics Engineering Managerto bridge the gap between complex data infrastructure and actionable business insights. In this pivotal role, you will lead the charge in defining our data modeling standards, ensuring data quality, and empowering our stakeholders with a robust, self-service data platform. If you are passionate about applying software engineering best practices to data analytics and leading high-performing teams, we want you to build the future with usMô tả công việc1. Team Leadership Culture:Lead, mentor, and grow a team of talented Analytics Engineers. You will be responsible for their career development, fostering a culture of continuous learning and technical excellence.Champion the "Data as a Product" mindset, ensuring that datasets produced by the team are treated with the same rigor and reliability as customer-facing software.Drive agile processes within the data team to ensure rapid delivery of value while maintaining high standards.2. Technical Strategy Architecture:Architect and maintain a scalable data modeling layer (using tools likesemantic) that transforms raw data into reliable, documented, and accessible datasets.Define and enforce coding standards, version control practices (Git), and CI/CD workflows for analytics code.Collaborate with Data Engineering to optimize data warehouse performance (e.g., BigQuery/Lakehouse) and manage compute costs effectively.3. Data Quality Governance:Implement automated testing and observability frameworks to detect data issues before they impact downstream users.Establish clear data lineage and documentation to democratize data access across the organization.Ensure strict adherence to data privacy, security, and compliance standards—a critical requirement in the Fintech sector.4. Cross-Functional Collaboration:Partner closely with Product Managers, and Business Leaders to translate complex business requirements into technical data solutions.Act as a technical advisor, helping stakeholders understand the "art of the possible" with our data stack.Yêu cầu công việcExperience:5+ years of experience in the Data domain, with at least 2 years in a leadership or management role.Technical Mastery:Expert-level SQL skills and deep understanding of query optimization.Hands-on experience with Cloud Data Warehouses (Google BigQuery)Workflow Orchestration:Hands-on experience with orchestration tools such asAirflow, n8n.You should be capable of designing complex, dependency-aware pipelines that are resilient to failure.BI Semantic Layer Integration:Deep understanding of how data is consumed by BI tools (e.g.,Looker...). Ability to design the 'Semantic Layer' to ensure consistent metrics across the organization.Soft Skills Culture FitStakeholder Management:"Ability to manage expectations with C-level executives and negotiate priorities effectively in a fast-paced environment."Talent Acquisition:"Experience in recruiting top-tier engineering talent and building a diverse, high-performing team from the ground up."

Responsible for PBI (PowerBI) development activity Extract Data from sources Transform raw data into usable data Modeling data which follows data science theory Load data to PBI, then perform Visualization regarding to customer request Responsible for PBI operation activity Answer customer concerns Consult for customer concern or requests Perform bug/issue fixing Apply new minor change for existing PBI Providing dataset maintenance Provide data freezing (depending on customer requirement) Responsible for SQL Server development Perform Design Database based on Customer requirement Responsible for ETL (Extract-Transform-Load) Responsible for SQL Server Operations Responsible for database maintenance Provide DML process (fixing/data) correction in case of customer requirementWHY BOSCH? Because we do not just follow trends, we create them. Together we turn ideas into reality, working every day to make the world of tomorrow a better place. Do you set high expectations for your learning journey? So do we. At Bosch, you’ll explore, grow, and challenge yourself in a dynamic and innovative environment. Internship Benefits Learning Opportunities at Bosch Monthly Internship Allowance, plus Meal and Parking support. 1 paid leave day + 1 sick leave day for each internship month. 1 birthday leave day if your birthday falls during the internship period. Accident insurance provided throughout the internship. Opportunity to observe and engage in international projects and innovation. Access to our diverse training programs which surely help strengthen both your personal and professionalism. Participation in various company activities such as football, yoga, badminton, and team building.

Minimum qualifications: Bachelor's degree in Computer Science, or equivalent practical experience. 5 years of customer-facing experience designing and deploying distributed data processing systems with one or more technologies. Experience with SQL data bases (e.g., PostgreSQL, MySQL, Oracle) and NoSQL data bases (e.g., Mongo, Cassandra.). Experience with different types of data modeling techniques and methodologies for traditional Online Analytical Processing or Online Transaction Processing (OLAP/OLTP) databases and modern data warehouses. Preferred qualifications: Certification in Cloud. 5 years of experience in managing technical client service. Experience reading software code in one or more languages such as Java, Python, NodeJS, Golang, JavaScript. Experience in devising migration approaches, and migrating on premise data processing systems to Cloud. Experience designing and deploying large-scale distributed data processing systems with one or more technologies: Oracle, SQL Server, MySQL, PostgreSQL, MongoDB, Cassandra, Redis, Hadoop, Spark, Flink, Kafka, Druid, Hive, HBase, Vertica, Netezza, Teradata, Tableau, or MicroStrategy. Knowledge of building and operationalizing data pipelines. About the jobThe Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive. We help customers transform and evolve their business through the use of Google’s global network, web-scale data centers, and software infrastructure. As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners. In this role, you will work with customers on critical projects to transform their business with data. You will provide consulting, solution design, and technical program management capabilities to customer engagements while directing customer executives and technical stakeholders on project related decisions. You will serve as a liaison between our customers and product teams to drive product excellence and adoption. In addition, you will also work with Google partners currently servicing accounts to manage programs, deliver consulting services, and provide technical guidance.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 Work with customer technical leads, client executives, and partners to manage and deliver successful implementations of cloud solutions becoming a trusted advisor to decision makers throughout the engagement. Work with internal specialists, product and engineering teams to package best practices and lessons learned into thought leadership, methodologies, and published assets. Interact with business, partners, and customer technical stakeholders to manage project scope, priorities, deliverables, risks/issues, and timelines for successful client outcomes. Propose solution architectures and manage the deployment of cloud based databases, big data, and analytics solutions according to customer requirements and implement best practices. Travel up to 40% of the time for client engagements as needed. 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 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.

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.

We are seeking a highly skilled Senior Business Intelligence Analyst with a strong experience in  E-commerce or high growth start-up companies; or candidates with strong digital marketing or product analytics background. This role requires close collaboration with cross-functional stakeholders—particularly in Product, Campaign, FPA, and Demand Planning—to define data needs, ensure effective tracking, conduct A/B testing, and develop robust insights that guide strategic decisions.  BI Data Modeling: Design and develop scalable data marts and data pipelines with aligned metrics to support new product initiatives and analytics use cases.Build and own end-to-end data pipelines from raw event data to business-ready tables, ensuring reliability, performance, and testability.Define and standardize core business metrics — GMV, conversion rate, DAU, funnel KPIs — to create a single source of truth across teams.Demand Growth Analysis: Conduct deep-dive analyses to identify growth levers, surface demand trends, and generate actionable recommendations for marketing, product, and commercial strategies.Design, execute, and evaluate A/B tests end-to-end: hypothesis formation, power analysis, experiment design, result interpretation, and post-experiment monitoring.Proactively identify anomalies, shifts in business performance, and leading indicators that require stakeholder attention.Dashboard and Reporting: Develop and maintain dashboards, reports, and data visualizations to monitor key performance and business metrics.Deliver ad-hoc analyses to address critical business questions, uncover trends, and support decision-making processes.Translate complex data into clear, actionable insights tailored for both technical and non-technical stakeholders.Continuous Improvement:Continuously enhance BI processes by leveraging advanced tools, including AI-driven solutions, to improve productivity and analytical capabilities.Mentor and guide junior team members to strengthen their technical and analytical skills, fostering a culture of continuous learning and improvement.Qualifications:

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.

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.

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.

Mô tả công việcBuilding Machine Learning models using your core expertise;Collaborate with Product and Business to define the Machine Learning product, focus on Fraud/Risk management and Financial Services;Collecting, cleaning, preparing data at large scale for modeling;Adding new features, exploring new approaches to keep pushing the model performance;Participating in productionizing Machine Learning models for live production;Designing, conducting A/B tests and analyzing the results for experiment insights;Building pipelines for continuously validating and updating models.Yêu cầu công việc3+ years working experience with 2 years hands-on with ML, or 2+ years with PhD degree;Good understanding of mathematical foundations of Machine Learning algorithms;Have practical experience in applying Machine Learning in Fraud/Risk management, credit scoring or user behavior analysis;A builder. You go the extra mile to bring your prototypes to production;Strong product ownership. You take a high responsibility for what you build. You keep a high bar for product quality;Strong collaboration skills. You reach out to help other team members; Familiar with using genAI in analytics/modeling and coding;Experience with financial service models is a plus.