We are hiring a Senior Data Scientist to join Masan's central Data team, working on large-scale data problems across retail, FMCG, supply chain, and consumer platforms.
This role is designed for candidates with a strong algorithmic foundation and experience working with large-scale systems, who want to apply their expertise to real business problems with measurable impact.
You will work on end-to-end machine learning solutions, from problem framing and model development to deployment and performance monitoring. While this is a full-stack data science role, you will collaborate closely with Data Engineers, ML Engineers, and Product teams rather than working independently on infrastructure.
Key Responsibilities
- Translate complex business problems into data science and machine learning solutions
- Design, build, and optimize models such as: recommendation and ranking systems; forecasting and demand prediction models; segmentation and scoring models
- Work with large-scale datasets and distributed systems to support production use cases
- Participate in building and improving end-to-end ML pipelines (training, deployment, monitoring)
- Collaborate with engineering teams to ensure models are scalable, stable, and maintainable
- Analyze model performance, identify issues, and continuously improve results
- Communicate insights, trade-offs, and technical decisions clearly to stakeholders
Requirements
Must-have
- 47+ years of experience in Data Science, Machine Learning, or related fields
- Strong foundation in algorithms, data structures, and applied statistics
- Proven experience working with large-scale systems or high-volume data
- Hands-on experience building and deploying production ML models
- Strong Python skills and experience with ML frameworks (e.g. PyTorch, TensorFlow, Scikit-learn)
- Experience working with distributed data processing (Spark, PySpark, or similar)
- Ability to work effectively with engineers and product teams in complex systems
- Strong problem-solving mindset and ability to reason from first principles
- Comfortable working with ambiguity and evolving requirements
- Able to balance technical excellence with business impact
- Ownership mindset with strong collaboration skills
Preferred
- Experience building recommendation systems, ranking, or personalization models
- Background from big tech, platform companies, or large-scale digital products
- Familiarity with ML deployment tools (MLflow, Docker, FastAPI, CI/CD pipelines)
- Experience with cloud platforms (Azure, AWS, or GCP)
Key note: We understand that senior candidates often consider timing carefully. Start dates are flexible, and we are open to discussing transition plans.
