Quantium Starter Repo

Problem

Analytics projects often become difficult to hand over because file structure, naming, and workflow conventions vary across contributors. This reduces reproducibility and slows team velocity.

Approach

I created a starter repository with clear folder conventions, repeatable notebook flow, and practical templates for analysis tasks. The design emphasizes maintainability and easy onboarding for future contributors.

Key Highlights

• Built a structured starter template for repeatable analytics workflows.
• Standardized project organization to reduce setup overhead in new analysis tasks.
• Improved reproducibility through consistent notebook and data handling patterns.

Lessons Learned

• Standards and naming conventions are essential for team handovers.
• Templates cut project setup time and increase delivery consistency.
• Reproducibility should be treated as a first-class engineering requirement.

Tech Stack

• Python
• SQL
• Data Wrangling

Outcome

The repository improves analysis consistency, shortens setup time for new projects, and provides a clean base for expanding into larger data engineering workflows.