RESUME LAYERING
Resumes are too flat, they chronicle a person’s employment history, but don’t do a fair job quantifying the skills, experience, and tools the person cultivated while in the position. The emergence of AI and its inclusion in the hiring process to render a resume to fit a posting, shows how ineffectual and static the current approach to resumes really is. This is a first draft of a new resume format. It takes a layered approach, where the individual is represented not only by a chronicle of work experience, but also through an analytics dashboard. Skills and tools are captured based on the roles held and experience points are calculated to give a better estimation of how comfortable the candidate is with each skill they learned.
The plan is to continue iterating on this. Right now experience points are calculated based on a simple quantification method*.
*Point-Based System (Simple Quantification):
Formula: For each skill, calculate Points = (Difficulty to Learn + Difficulty to Use) / 2 * Years of Experience * Mastery Factor (e.g., 0 for beginner, 1 for intermediate, 2 for expert—self-assessed).
Example: For "Python Scripting" (Learn: 60, Use: 65, Years: 10), Average Difficulty = 62.5, Points = 62.5 * 10 * 1.5 = 937.5.