Data Scientist

qode.world

. Design robust, scalable, and innovative data science solutions considering performance, maintainability, and business impact .

Posted 10/13/2026full-timeHo Chi Minh • VietnamMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in data science project leadership, including end-to-end project ownership, mentoring, and collaboration with cross-functional teams. Proficient in Python, SQL, and relevant data science libraries, with a strong focus on translating complex data insights into actionable business strategies.

Highest-signal resume keywords

Data Science Project LeadershipExpert in Python and SQLExperience with MLOps ToolsAdvanced Data Visualization SkillsMentoring Junior Data Scientists

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningDeep LearningNatural Language ProcessingComputer VisionStatisticsProduction-Ready CodeData PreparationModel DevelopmentModel EvaluationOptimization

Soft Skills

Problem-SolvingStrong Communication SkillsProactive MindsetCollaborationStakeholder Engagement

Tools & Technologies

PandasNumPyScikit-learnTensorFlowPyTorchGitHubGitLabGCPAWSAzure

Industry Keywords

Data ScienceMLOpsAgile Delivery PracticesData VisualizationCloud Platforms

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesNumpyPandasPythonPyTorchScikit-LearnSQLTensorflow

About the role

Key responsibilities & impact

Design robust, scalable, and innovative data science solutions considering performance, maintainability, and business impact
Provide technical leadership on complex projects
Oversee the work of junior and mid-level data scientists and ensure best practices are followed
Own end-to-end data science projects and modules, from data collection and preparation through model development, evaluation, and MLOps
Communicate complex analytical concepts and findings to technical and non-technical stakeholders
Translate insights into actionable business recommendations
Collaborate with project managers, engineers, and business stakeholders to align data science efforts with business objectives
Engage senior stakeholders to understand business needs, present complex findings, and influence strategic data-driven decision-making
Stay current with advances in data science, machine learning, and AI and explore new technologies and methodologies
Mentor and coach Data Scientists at all levels

Requirements

What you’ll need

Bachelor’s degree in Mathematics, Statistics, Data Science, Computer Science, AI, Engineering, or a highly related field is required
Master’s degree in a related discipline is preferred
At least 5 years of experience in one or more data science domains, including machine learning, deep learning, NLP, computer vision, optimization, or statistics
Excellence in problem-solving and ability to formulate business problems into rigorous technical requirements
Proven experience leading data science workstreams or projects and mentoring junior data scientists
Fluent in English with strong communication skills, especially with non-technical stakeholders
Expert in Python and SQL and relevant data science libraries, including Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch
Ability to write production-ready code
Advanced version control skills using tools such as GitHub or GitLab
Advanced data visualization skills
Experience with MLOps tools and practices, including pretraining, model tuning, model packaging, CI/CD for ML, model monitoring, and ML pipelines
Hands-on experience with cloud platforms such as GCP, AWS, or Azure
Experience with containerization using Docker or Kubernetes
Ability to research publications and translate research papers into functional code
Strong proactive mindset and ability to take full responsibility for project outcomes
Ability to lead communication of technical concepts and collaborate with cross-functional teams
Ability to engage business stakeholders to gather domain knowledge and requirements and communicate timelines and results
Familiarity with agile delivery practices is a plus

Benefits

Comp & perks

Flexible hours with 5 working days per week (Monday–Friday), focused on output
Hybrid model with 2 work-from-home days per week (Monday and Friday)
12 days annual leave plus special seniority benefits
Lunch and gasoline support allowances
13th-month salary
Performance-based bonuses
Social, health, and unemployment insurance based on gross salary
Health insurance for the employee, with seniority-based extension to family members
Training for specialized skills, soft skills, and English
Monthly Happy Hours, company trips, and sport clubs (Soccer, Yoga, Badminton)
Annual health check-ups
Supportive, collaborative environment
Clear career progression into domain-specific expertise with AI and business knowledge
Variety of client choices for interaction and professional growth