Senior/Lead Data ScientistCompany: Vinsmart FutureOn-siteHo Chi Minh, Vietnam
Position Summary 

We are looking for a Senior/Lead Data Scientist with deep expertise in tabular data modeling, predictive analytics, and business intelligence. This role focuses on extracting actionable insights from structured datasets, developing scalable machine learning models, and improving decision-making across business operations. 

Key Responsibilities 

  • Develop predictive ML/AI models and advanced analytics solutions using structured/tabular datasets. 
  • Analyze large-scale relational data from business systems, customer platforms, financial records, and operational databases. 
  • Design and optimize machine learning pipelines for classification, regression, forecasting, and anomaly detection tasks. 
  • Perform feature engineering, data cleaning, imputation, and data quality validation on structured datasets. 
  • Collaborate with data engineers and analysts to improve data architecture and dataset usability. 
  • Build scalable solutions using SQL, Python, and distributed data processing frameworks. 
  • Conduct A/B testing and statistical analysis to support product and business decisions. 
  • Communicate analytical findings through dashboards, reports, and executive presentations. 
  • Mentor junior team members and establish best practices for structured data modeling and experimentation. 

Required Qualifications 

  • Master’s degree or higher in Data Science, Statistics, Computer Science, Mathematics, Economics, or a related quantitative field. 
  • 4+ years of experience working with structured/tabular data in production environments. 
  • Strong Python programming skills using Pandas, NumPy, Scikit-learn, and related libraries. 
  • Solid understanding of statistics, hypothesis testing, and experimental design. 
  • Experience handling high-volume datasets in cloud or distributed environments. 
  • Ability to translate business problems into measurable analytical solutions. 

Preferred Qualifications 
  • Experience with customer analytics, risk modeling, forecasting, or recommendation systems. 
  • Familiarity with feature stores and MLOps workflows. 
  • Knowledge of cloud platforms including AWS, Azure, or Google Cloud.