Data Scientist to Create Predictive Models for Customer Behavior Insights
Skills Required
Description
Understanding customer behavior goes beyond tracking clicks. It requires advanced predictive modeling that connects data points to real-world actions.
The project is focused on creating predictive models that can identify patterns, forecast outcomes, and help shape business decisions.
Python, Pandas, and Scikit-learn will be the primary tools used in developing these models.
The data scientist should have prior experience in cleaning, preparing, and structuring messy data before applying any algorithms.
Exploratory data analysis will be a key step. This helps surface hidden trends and determine which variables have the most impact.
Perform data wrangling and preprocessing
Run statistical tests to validate assumptions
Explore correlations between features
Create visualizations that explain findings
Predictive models should be both accurate and interpretable. Stakeholders should be able to understand not just the “what” but also the “why” behind predictions.
Feature engineering will likely be required. Derived metrics often provide stronger insights than raw data alone.
Accuracy must be balanced with overfitting risks. Models should generalize well across unseen data.
Train models with Scikit-learn pipelines
Apply cross-validation for reliability
Monitor performance with multiple metrics
Fine-tune hyperparameters for efficiency
Collabo...