Senior Data Scientist

About the Role

We are looking for a Senior Data Scientist to join Masan's centralized Data organization, driving advanced analytics and machine learning initiatives across retail, FMCG, supply chain, and consumer platforms.

In this role, you will own end-to-end development of data science and machine learning solutions — from business problem framing, data exploration, feature engineering, model development, deployment, to post-production monitoring and optimization.

You will work with large-scale, multi-domain enterprise data and collaborate closely with Data Engineering, Platform, Product, and business teams to deliver scalable, data-driven solutions with measurable business impact.

As Masan continues investing in enterprise AI capabilities, the Data Science team may also collaborate with broader AI initiatives when relevant to business use cases.

Key Responsibilities

• Translate business problems into scalable analytical and machine learning solutions with measurable impact.
• Perform exploratory data analysis (EDA), hypothesis generation, and insight validation using large-scale structured and unstructured datasets.
• Build, tune, evaluate, and optimize ML models across use cases such as forecasting, recommendation, segmentation, classification, optimization, and anomaly detection.
• Develop reusable features and contribute to enterprise Feature Store initiatives.
• Work with modern big-data environments such as Spark, PySpark, Databricks, and Delta Lake.
• Ensure data quality, consistency, and reliability across data and ML pipelines.
• Collaborate with Data Engineers and ML Engineers to productionize models and scale ML solutions.
• Deploy and maintain ML services using MLflow, FastAPI, Docker, and CI/CD workflows.
• Monitor model performance, data drift, and business KPIs after deployment, and continuously improve models based on production feedback.
• Communicate insights and recommendations clearly to both technical and non-technical stakeholders.
• Explore emerging technologies and advanced AI/ML techniques when relevant to business needs.

Qualifications

Senior Level

• 4+ years of hands-on experience in applied machine learning and advanced analytics.
• Proven track record of solving real business problems using end-to-end ML solutions.
• Strong Python skills (pandas, scikit-learn, PySpark).
• Solid understanding of statistics, machine learning algorithms, experimentation, and data structures.
• Experience deploying, monitoring, and optimizing ML models in production environments.
• Experience working with cloud or big-data platforms such as Azure, Databricks, Spark, or Delta Lake.
• Strong stakeholder management and communication skills.

Preferred

• Experience with ML deployment/MLOps tools such as MLflow, FastAPI, Docker, or Kubernetes.
• Exposure to modern AI technologies such as LLMs, embeddings, or RAG is a plus.
• Product mindset with strong ownership and business-oriented thinking.
• Experience in retail, FMCG, supply chain, or customer analytics is highly preferred.