Data Scientist, CDC

Siam Makro Public Company Limited

. Analyze data and develop machine learning solutions for demand forecasting .

Posted 11/6/2026full-timePhra Nakhon Si Ayutthaya • ThailandMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Proficient in Python and PySpark for data analysis and machine learning, with a strong understanding of regression and time series forecasting models. Capable of delivering end-to-end solutions while collaborating effectively with cross-functional teams and communicating insights to both business and technical stakeholders.

Highest-signal resume keywords

Python ProficiencyMachine Learning Workflow ExpertiseSQL SkillsData Visualization with Power BICloud Technologies (Databricks, Azure, AWS)

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning SolutionsRegression ModelsTime Series ModelsData CleansingFeature EngineeringModel EvaluationForecasting Metrics (MAPE, MAE)Large Dataset ManagementProduction Pipeline DevelopmentReal-Time Analytics

Soft Skills

Strong Communication SkillsOwnership and AccountabilityCollaboration

Tools & Technologies

Power BIDatabricksAzureAWSMLOps Tools (MLflow)

Industry Keywords

Demand ForecastingData VisualizationForecasting Evaluation MetricsClassical Time Series MethodsBusiness Impact Optimization

Tech Stack

Tools & technologies

AWSAzureCloudPySparkPythonSQL

About the role

Key responsibilities & impact

Analyze data and develop machine learning solutions for demand forecasting
Build and evaluate regression and time series models
Perform data cleansing and feature engineering
Validate model performance using forecasting metrics such as MAPE and MAE
Manage and query large datasets using SQL
Create data visualizations using tools such as Power BI
Use cloud-based technologies including Databricks, Azure, or AWS
Explain insights and models to business and technical teams
Deliver end-to-end solutions, not just analysis
Collaborate with Data Engineering, Tech, Product, and Supply Chain teams
Potentially build production forecast-output pipelines and support downstream systems
Potentially work with real-time analytics or scheduled processing systems

Requirements

What you’ll need

Proficiency in Python and PySpark for data analysis, machine learning, and demand forecasting (regression + time series models)
Experience with forecasting models such as LightGBM/XGBoost and classical time series methods (e.g., ETS/ARIMA)
Strong understanding of the machine learning workflow (data cleansing, feature engineering, model evaluation, model explainability)
Familiarity with forecasting evaluation metrics (e.g., MAPE, MAE) and ability to validate model performance
Strong SQL skills for managing and querying large datasets
Knowledge of data visualization tools (e.g., Power BI)
Experience with cloud-based technologies such as Databricks, Azure, or AWS
Strong communication skills — able to explain insights and models to both business and technical teams
Ownership and accountability — able to deliver end-to-end solutions, not just analysis
Collaboration — able to work effectively with Data Engineering, Tech, Product, and Supply Chain teams
Preferred (Optional): Exposure to MLOps tools (e.g., MLflow, job scheduling)
Preferred (Optional): Experience building production pipelines for forecast outputs (daily/weekly runs) and supporting downstream systems
Preferred (Optional): Experience in real-time analytics or scheduled processing systems
Preferred (Optional): Optimization mindset — able to balance accuracy, business impact, and time constraints

Benefits

Comp & perks

Clear focus.
Diverse Workplace (Our members are from around the world!)
Non-hierarchical and agile environment
Growth opportunity and career path