Junior Data Scientist for Python Tasks

I’m looking for a junior-level data scientist who is comfortable working end-to-end in Python and its key libraries (Pandas, NumPy, scikit-learn, Matplotlib, Seaborn, etc.). The work will cover three main areas:

• Data cleaning and preparation
• Exploratory analysis with clear, insightful visualizations
• Building and evaluating predictive models that can be handed off for production use

You’ll receive raw datasets along with a brief describing the business questions. I’ll need you to:

1. Inspect and clean the data, documenting every assumption and transformation.
2. Produce visual summaries that highlight trends, anomalies, and any correlations worth noting.
3. Develop at least one baseline predictive model, iterate to improve performance, and deliver a concise report explaining feature importance, metrics, and next steps.

Please share a short note on similar work you’ve done, the Python libraries you prefer for each stage, and an estimated timeline. Code should be well-commented and delivered in Jupyter notebooks or .py scripts, with a final PDF or HTML report summarizing findings.