Project Management In Data Science

A good data scientist must leverage good project management to best optimize their time as they run to the finish line. My new project starts with a good scope of what needs to be done at a high level. Here’s my work breakdown structure (WBS) of what needs to be accomplished in the next week and a half. Let’s do it!

1.0.0 Design & Iterator Framing

1.1.0 Clearly Define Scope (Exchanges, Sectors, Cap Size)

1.2.0 Sectors

1.3.0 Stocks within Sectors

1.4.0 Financial Metrics Characteristics per Stock

1.5.0 Stocks Last 10-Q Results EoD Price

1.6.0 Stock’s Previous 10-Q EoD Price

2.0.0 URL builder

2.1.0 Build URLs to Stocks

2.2.0 Build URLs to Stocks Financial Metrics

3.0.0 RPA Scraping

3.1.0 Selenium Traveler

3.2.0 Soup Scraper

4.0.0 Data Structures

4.1.0 Scraped Data Landing DF

4.2.0 Data Cleaning

4.3.0 Derivative Measures based on scraped data

4.4.0 Data Discarding and documentation

4.4.0 Pandas Final Framing for Regression

5.0.0 Calculations and Output

5.1.0 Regression

5.2.0 Output Requirements

6.0.0 Presentation

6.1.0 Requirements

6.2.0 Compelling Selling Point to Make

6.3.0 Blog Post