https://0xthijs.github.io/tags/python/Recent content in Python on Thijs van der AaHugo -- 0.159.0en-usWed, 18 Feb 2026 00:00:00 +0000https://0xthijs.github.io/projects/skillflex/Wed, 18 Feb 2026 00:00:00 +0000https://0xthijs.github.io/projects/skillflex/An AI-native marketplace that infers employee skills from unstructured data to automatically match talent with internal projects, reducing attrition.https://0xthijs.github.io/projects/burnout-risk/Mon, 09 Feb 2026 00:00:00 +0000https://0xthijs.github.io/projects/burnout-risk/A predictive risk model that aggregates commute, overtime, and stagnation data to identify potential attrition, proving 4x more effective than random sampling.https://0xthijs.github.io/projects/critical-talent-radar/Sat, 14 Feb 2026 00:00:00 +0000https://0xthijs.github.io/projects/critical-talent-radar/An AI-powered retention tool that identifies at-risk high performers and generates personalized retention strategies.https://0xthijs.github.io/projects/data-governance/Sun, 15 Feb 2026 00:00:00 +0000https://0xthijs.github.io/projects/data-governance/An automated ‘Governance Engine’ acting as a firewall for HR data, implementing a ‘Chaos Monkey’ to stress-test data integrity.https://0xthijs.github.io/projects/diversity-audit/Mon, 09 Feb 2026 00:00:00 +0000https://0xthijs.github.io/projects/diversity-audit/A rigorous audit of the Gender Pay Gap and Leadership Representation, uncovering a ’leaky pipeline’ despite achieving pay equity.https://0xthijs.github.io/projects/ibm-attrition/Mon, 09 Feb 2026 14:30:00 +0700https://0xthijs.github.io/projects/ibm-attrition/A deep-dive analysis challenging retention myths, revealing that ‘High Performers’ are 16% more likely to leave than average employees.https://0xthijs.github.io/projects/one-on-one-architect/Sun, 15 Feb 2026 00:00:00 +0000https://0xthijs.github.io/projects/one-on-one-architect/A Streamlit tool designed to restructure manager meetings, transforming unstructured chats into strategic career conversations.https://0xthijs.github.io/projects/promotion-velocity/Mon, 09 Feb 2026 00:00:00 +0000https://0xthijs.github.io/projects/promotion-velocity/A counter-intuitive analysis of the ‘Promotion Paradox’, revealing that high performers are 17% more likely to leave immediately after a promotion.