Project description:

Intractive project that tells about gender pay gap in Russia. Based on 8 million records from lagrest russian recrutment service, HH.ru, it recounts the differences in every specialisation and tells their reasons. The main insight of this work is that women in Russia often doesn’t even submit their resume to the most paid vacancies. The higher the salary in the vacancy, the less percent of women tries to get this work. The project is also unique because of this user-intecation part: you can specify your salary, region and profession and compare your salary with the salary from o resume and

Impact reached:

The article became extremely popular at Tinkoff Journal and get the most likes in June.

We also made small continuation tellling about age salary ceiling:

https://journal.tinkoff.ru/stat-ageism/

Techniques/technologies used:

Data Analysis and Investigate: Tableau, Python, Google Docs
Data Visualisation: Tableau, Figma, Vanilla JS, React, Scrollytelling

What was the hardest part of this project?

The hardest part of the project was coding: it was pretty difficult to make all graphs and animations work smoothly and connect them with real-time calculations based on user salsry

What can others learn from this project?

Using of ‘big data’ in ivestigations, using of scrollytelling, using of ‘me-layer’ in project

Project links:

journal.tinkoff.ru/gender-gap/

journal.tinkoff.ru/stat-ageism/