Data Scientist for Predictive Sales Analysis
Skills Required
Description
Understanding sales trends before they happen is the central challenge of this project. The data scientist will be tasked with developing predictive models that help anticipate customer behavior and revenue shifts.
Python will be the main language for this work, leveraging frameworks such as Scikit-learn, Keras, and PyTorch. Strong knowledge of these libraries will be crucial for building, training, and testing models efficiently.
The role involves a mix of machine learning and deep learning. Traditional models may work in some cases, while more complex neural networks may be necessary for high-accuracy forecasts.
NLP techniques could also be used to analyze text-based sales data, such as customer feedback or support tickets, to uncover sentiment patterns linked to purchasing decisions.
Working with structured and unstructured data will be expected. Pandas will be heavily relied upon for cleaning, manipulation, and exploratory analysis.
Collaboration with the business team will ensure models align with practical sales goals rather than academic accuracy alone. Predictions should be actionable.
Computer vision may also come into play if image-based product or retail data needs to be processed as part of the forecasting pipeline.
Clear communication will be essential. Complex models and outputs should be translated into straightforward insights that non-technical stakeholders can understand.
Timeliness is i...