Data Scientist for Predictive Demand Models
Skills Required
Description
Forecasting future demand requires both technical accuracy and business understanding. The Data Scientist for Predictive Demand Models will play a key role in helping organizations anticipate sales trends and optimize inventory decisions.
You’ll use Python, Pandas, and Scikit-learn to process large datasets and extract actionable insights from historical performance.
Model development will focus on demand prediction, trend identification, and anomaly detection.
Your work will involve cleaning, transforming, and structuring data for modeling efficiency.
Machine learning algorithms such as regression, ARIMA, and ensemble methods will be part of your toolkit.
You’ll also evaluate new techniques to improve model accuracy and reduce forecasting error.
Data visualization will help translate complex patterns into clear visuals using Matplotlib, Seaborn, or Tableau.
Collaboration with business and operations teams will ensure your insights align with practical use cases.
Understanding seasonality and external market influences will be crucial for refining your models.
You’ll apply SQL for data extraction, query optimization, and performance tuning.
Feature engineering will play a large role in identifying key variables that impact demand.
Testing and validation will be ongoing — models should perform well across different data subsets.
Documentation and reproducibility will be ...