Data Scientist

Featured Job

Lead Data Engineer

Ho Chi Minh, Ha Noi - Viet Nam

Outsource

• Data Engineering
• Management

Design, create, and maintain scalable data infrastructure, which includes data lakes, pipelines, and metadata repositories, to ensure accurate and timely delivery of data to stakeholders. Collaborate with data scientists to develop and maintain data models, integrate data sources, and facilitate machine learning workflows and experimentation environments. Build and enhance large-scale, batch, and real-time data processing systems to improve operational efficiency and align with business goals. Use Python, Apache Airflow, and AWS services to automate data workflows and processes, ensuring efficient scheduling and monitoring. Utilize AWS services like S3, Glue, EC2, and Lambda to manage data storage and compute resources, striving for high performance, scalability, and cost-effectiveness. Implement comprehensive testing and validation methods to guarantee the reliability, accuracy, and security of data processing workflows. Keep updated on the latest industry best practices and emerging technologies in data engineering and data science to suggest innovative solutions and enhancements.

Negotiation

Data Experience Lead

Ho Chi Minh - Viet Nam

Product

• Project Management
• Business Analyst
• Data Analyst

Train pods in designing, building, deploying, and maintaining Data Products based on established playbooks. Simplify and translate platform playbooks into actionable user guides. Assist teams transitioning into new Data Mesh roles (DPO, Steward, Data Architect, Analytics Engineer, etc.). Provide hands-on support for early-wave or complex Data Products. Make data products and platform accessible and engaging for all staff across the organization. Develop a digital enablement portal including guides, checklists, templates, and videos. Create structured training pathways and capability improvement programs for all affected staff/users. Generate clear visual materials such as diagrams, flows, web-style docs, and promotional videos to aid adoption and understanding. Facilitate onboarding, workshops, roadshows, Q&A sessions, town hall presentations, and demos. Offer structured guidance across ingestion patterns, medallion design, semantics, quality, and metrics to ensure consistency in a mesh environment. Execute or coordinate targeted POCs for pods needing specialized help. Identify and communicate reusable patterns back to the Data Mesh Platform Team. Organize Showcases to create visibility, excitement, and promote reuse. Oversee the end-to-end user experience design for the Data Mesh Platform, aiming for clarity, trust, and ease of use. Shape how users discover, understand, and interact with data products across domains. Maintain UX standards in partnership with the customer-facing UX Design team. Take a deeply user-centric approach to drive change through intuitive and guided technology. Engage with end users to understand needs and gather insights. Integrate continuous feedback loops and iterate quickly to improve platform usability. Ensure all Mesh Experience features support adoption and reinforce the "data-as-a-product" mindset. Maintain active channels for communication and updates. Communicate expectations, standards, and timelines clearly. Highlight wins and success stories to build momentum. Curate relevant external content to support the transformation. Monitor progress of rollout, leader boards, and raise blockers with appropriate stakeholders. Utilize data to highlight platform adoption, culture change, wins, and challenges. Produce clear and compelling summaries on adoption progress for decision making. Manage end user feedback and be the link between users and the platform team.

Negotiation

Featured Job

Data Scientist Lead

Ho Chi Minh - Viet Nam

Outsource

• Machine Learning
• Data Engineering
• Cloud
• Management

Creating robust ETL/ELT data pipelines for structured and unstructured data Developing interactive dashboards and visualizations for effective communication of insights Evaluating, deploying, and evaluating machine learning and/or generative AI models Applying statistical analysis and mathematical modeling to extract insights from complex datasets Working with various teams to deliver data-driven solutions Creating and maintaining scalable ML pipelines and APIs for real-time and batch inference Ensuring best practices in model versioning, reproducibility, observability, and governance (MLOps) Staying updated with AI/ML trends and contributing to projects involving semantic search, knowledge graphs, or retrieval-augmented generation as necessary.

Negotiation