When Finance Speaks Python: Mapping Python Integration in Finance Degrees and the University–Industry Skills Gap

Author: Veliota Drakopoulou
Affiliations: Higher Colleges of Technology (UAE); Embry-Riddle Aeronautical University (USA)
ORCID: https://orcid.org/0000-0002…
Correspondence: vdrakopoulou@yahoo.com
GitHub: https://github.com/vdrakopo…

GitHub repository: https://github.com/vdrakopo…

 Replication Package DOI: https://doi.org/10.5281/zen…

Overview

This replication package accompanies the article "When Finance Speaks Python: Mapping Python Integration in Finance Degrees and the University–Industry Skills Gap."

The study examines 140 finance-related university programmes across 19 countries and compares curriculum-level Python integration with computational skill signals extracted from 190 finance and FinTech job advertisements. Using a novel Depth–Scope–Authenticity (DSA) rubric, the project investigates how universities respond to growing employer demand for programming, analytics, machine learning, and algorithmic finance skills.

Contents

• Scored curriculum dataset (140 programmes)
• Job-advert skill-signal dataset (190 records)
• Python replication code
• Tables and figures from the manuscript
• Rubric documentation and appendices
• Reproducibility files and SHA-256 checksums

Key Finding

Python is increasingly visible in finance education, but access to authentic computational learning remains highly uneven, suggesting that higher education may both close and reproduce digital skills gaps in finance.

Figure

 

Mean Python Curriculum Index (0–1)

United Kingdom            ████████████████████████████ 0.58
United States                 ██████████████████████████   0.53
Germany                        ████████████████████████     0.48
Kenya                             ███████████████████████      0.46
Brazil                              ██████████████████████       0.44
Russia                             ██████████████████████       0.44
Switzerland                     ██████████████████████       0.43
India                                ██████████████████████       0.43
South Africa                    █████████████████████        0.42
Nigeria                            █████████████████████        0.42
Egypt                               █████████████████████        0.42
Japan                               ████████████                 0.25
Hong Kong SAR              ██████████                   0.20
Australia                          ██████████                   0.20
China                               ███████                      0.14
Saudi Arabia                    ██                           0.05
United Arab Emirates      ██                           0.04
Ghana                                          0.00
Uganda                                         0.00

Figure: Cross-national variation in documented Python integration across finance programmes.

Citation

Drakopoulou, V. (2026). When Finance Speaks Python: Mapping Python Integration in Finance Degrees and the University–Industry Skills Gap. Replication Package. Zenodo. https://doi.org/10.5281/zen…