7 часов назад
Demand Planning Data Scientist
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Demand Planning Data Scientist (Demand Forecasting/ML): Building statistical and predictive models for product-order forecasting to generate reliable signals for inventory and supply plans with an accent on machine learning, statistical analysis, and large-scale data insights. Focus on validating and productionizing forecasting models, analyzing forecast accuracy and bias, and communicating data-driven recommendations to cross-functional business teams.
Location: Malaysia, Penang; remote work option available
Company
is hiring for a data science role supporting integrated business planning and demand forecasting.
What you will do
- Develop and implement predictive and statistical models to forecast product orders across geographies.
- Use historical data, machine learning, market intelligence, and field sales input to improve demand forecasts.
- Analyze forecast accuracy, bias, value add, and integrated business planning deviations with demand planners.
- Design experiments, validate model performance, and prepare statistical models for regular production use.
- Analyze large datasets to identify trends, patterns, and business insights through visualizations and reports.
- Recommend improvements to data collection, integration, retention, and data-driven planning processes.
Requirements
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
- Typically 1–2+ years of experience in data science or equivalent work experience.
- Extensive knowledge of predictive modeling, machine learning, and statistical analysis.
- Programming proficiency in Python, R, or SQL.
- Ability to collaborate with demand planners and cross-functional business stakeholders.
Culture & Benefits
- Full-time weekly schedule with a day shift.
- Remote work option available.
- Occasional travel may be required.
- Ongoing position with no stated end date.
- Pay is determined by role, level, location, skills, experience, and education or training.
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