Data Analytics · Machine Learning · 2025

A data-driven investigation into which human skills will survive automation. Analyzing global employment trends from 2010–2025, this project builds a Skill Survival Probability model that classifies every skill into one of four futures.

PythonPower BIMachine LearningData CleaningEDALabor Economics

Project Type

Research · Analytics

Duration

2025 (Ongoing)

Data Period

2010 – 2030

Role

Solo Researcher & Developer

Status

In Progress — EDA Phase

01Project Phases

✓ Complete

01

Data Collection

Sourced ai_impact_jobs_2010_2025.csv covering global job and skill trend data across 15 years.

✓ Complete

02

Data Cleaning

Produced cleaned_skill_data.csv — handled nulls, standardized formats, removed duplicates.

→ In Progress

03

Deep-Dive EDA

Uncovering trends in skill demand shifts, sector-level automation impact, and temporal patterns.

Upcoming

04

Model Building

Building Skill Survival Probability classifier using ML — labeling skills as future-proof, stable, at-risk, or obsolete.

Upcoming

05

Dashboard + Report

Interactive Power BI dashboard and final comprehensive research report.

02Skill Classification System

Category

Definition

Characteristics

Examples

Future-Proof

Skills with rising demand even post-2025

High creativity, judgment, interpersonal depth

AI Prompt Engineering, Strategic Leadership

Stable

Steady demand, low automation risk

Complementary to AI systems

Python, Critical Thinking, Project Management

At-Risk

Declining demand, partial automation possible

Routine, rule-based, moderate complexity

Basic Data Entry, Manual Reporting

Likely Obsolete

Strong downward trend, high substitution probability

Fully automatable, low cognitive demand

Manual Invoice Processing, Switchboard Operation

03Dataset Overview

ai_impact_jobs_2010_2025.csv → cleaned_skill_data.csv

Raw global employment and skill-demand data cleaned into a structured analytical dataset ready for EDA and modeling.

15

Years of Data

2010

Start Year

4

Skill Categories

04Tools & Technologies

Python

Pandas, NumPy, Scikit-learn for data processing and ML modeling

Power BI

Interactive dashboard for visualizing skill survival trends and predictions

EDA

Matplotlib, Seaborn for exploratory visualization and pattern discovery

Machine Learning

Classification model to compute Skill Survival Probability scores

05Expected Outcomes

Skill Survival Probability Model

A trained ML classifier that assigns each skill a survival probability score and a label — future-proof, stable, at-risk, or obsolete — based on historical demand patterns.

Power BI Dashboard

An interactive dashboard showing sector-wise skill obsolescence rates, temporal demand shifts, and 2030 forecasts — designed for HR professionals, researchers, and career planners.

Trend Analysis (2010–2025)

Deep-dive EDA uncovering which sectors and skill types were most disrupted by AI adoption, and the inflection points at which demand shifted.

Research Report

A comprehensive written report documenting methodology, findings, model performance, and actionable recommendations for future workforce planning and skill development.