Data Scientist for Demand Forecasting
Skills Required
Description
Understanding future demand is key to making better business decisions, and that’s exactly where your expertise comes in. We’re looking for a data scientist who can design and implement forecasting models using historical data, seasonal trends, and real-time signals. You’ll work with structured and unstructured datasets, applying Python, Pandas, and Scikit-learn to identify predictive patterns that improve accuracy and reduce uncertainty. The goal is to deliver clear, data-driven insights that directly influence product planning, inventory control, and financial forecasting.
Core Responsibilities:
Collect, clean, and structure large datasets for analysis using SQL and Python.
Build time-series and regression-based forecasting models with Scikit-learn.
Analyze trends, seasonality, and external variables that affect demand.
Visualize insights through charts, dashboards, and interactive reports.
Collaborate with stakeholders to translate data findings into business recommendations.
Precision, scalability, and interpretability will guide your work. You’ll be expected to document model logic, evaluate accuracy metrics, and iterate on performance improvements over time. Strong communication skills are essential, as you’ll often explain complex concepts to non-technical audiences.
Preferred Skills and Tools:
Expertise in data visualization tools like Matplotlib, Plotly, or Power BI.
Solid under...