Data Scientist (CDC)

Makro PRO Open

On-site Phra Nakhon Si Ayutthaya Full-time Mid-level Data Science

At a glance

Mid-level Data Science role at Makro PRO. Phra Nakhon Si Ayutthaya · full-time.

Pay not stated Data Scientist salary

RoleData Science

SeniorityMid-level

LocationPhra Nakhon Si Ayutthaya

WorkplaceOn-site

EmploymentFull-time

PostedNov 5, 2026

Role brief

dataroles summary, based on the employer's posting.

What you'll do

Build demand forecasts with regression, time-series methods, LightGBM or XGBoost
Prepare data and engineer features, then evaluate and explain model results
Use forecasting metrics such as MAPE and MAE to check model performance
Query large datasets with SQL and share findings with business and technical teams
Work with data engineering, tech, product and supply chain teams to deliver solutions

What you bring

You’re proficient in Python and PySpark for analysis, machine learning and demand forecasting
You bring strong SQL skills for handling and querying large datasets
You understand the machine-learning workflow, including cleansing, feature creation and model evaluation
You can validate forecast performance with metrics such as MAPE or MAE

Who this fits

This mid-level, full-time role is based on-site in Phra Nakhon Si Ayutthaya, Thailand. It suits someone who can take forecasting work through to delivery and explain model findings to both technical and business teams.

From the employer

Requirements

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) Qualifications:

Exposure to MLOps tools (e.g., MLflow, job scheduling)
Experience building production pipelines for forecast outputs (daily/weekly runs) and supporting downstream systems
Experience in real-time analytics or scheduled processing systems
Optimization mindset — able to balance accuracy, business impact, and time constraints

Benefits