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Job Title:
Expert Data Scientist – Demand Planning & Forecasting (Machine Learning)
Project:
Demand Planning ML Models Initiative
Role Level:
Expert / Principal (Hands-on, Delivery-Focused)
Employment Type:
Full-Time
Experience:
7+ Years
Job Location:
Remote
Job Timing:
Vietnam Time Zone
We are seeking an Expert Data Scientist with deep hands-on experience in machine learning–based demand forecasting to support the ANZ Demand Planning ML Models initiative .
This role requires a senior practitioner capable of
independently designing, developing, and delivering enterprise-grade demand forecasting models
. The ideal candidate will own forecasting solutions end-to-end and help improve business decision-making through highly accurate predictive models.
Lead the design, development, and optimization of ML-based demand forecasting models .
Work extensively with time-series datasets related to sales, demand, and supply planning .
Apply and optimize statistical forecasting techniques and machine learning algorithms .
Perform advanced feature engineering incorporating seasonality, trends, promotions, pricing, holidays, and external drivers.
Conduct
back-testing, validation, and scenario analysis
to continuously improve forecast accuracy.
Own the end-to-end data science lifecycle , from data exploration and model development to deployment support.
Define, monitor, and optimize forecasting KPIs including MAPE, RMSE, and MAE .
Review, validate, and refine forecasting methodologies to ensure accuracy and scalability.
Clearly communicate
model logic, assumptions, and insights
to business and executive stakeholders.
Collaborate closely with Data Engineers, Analytics teams, and business stakeholders to operationalize forecasting models.
Support production deployment, monitoring, and model performance improvements .
Drive
knowledge sharing and best practices
in forecasting and machine learning across teams.
7+ years of experience in Data Science / Machine Learning .
5+ years of hands-on experience in demand forecasting or demand planning using machine learning .
Proven experience delivering production-grade or business-critical forecasting models .
Strong experience working with
enterprise-scale time-series datasets
.
Advanced Python for Data Science and Machine Learning .
Strong expertise in time-series forecasting techniques (statistical and ML-based).
Experience with machine learning models such as regression, tree-based models, and ensemble methods .
Advanced feature engineering for demand and planning datasets .
Strong SQL and data manipulation capabilities.
Experience with
forecast evaluation metrics (MAPE, RMSE, MAE)
.
Strong ownership and accountability mindset .
Excellent analytical and problem-solving capabilities .
Ability to communicate complex technical concepts to non-technical stakeholders .
Comfortable working in fast-paced environments with tight delivery timelines .
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