Python

An AI-native marketplace that infers employee skills from unstructured data to automatically match talent with internal projects, reducing attrition.

A predictive risk model that aggregates commute, overtime, and stagnation data to identify potential attrition, proving 4x more effective than random sampling.

An AI-powered retention tool that identifies at-risk high performers and generates personalized retention strategies.

An automated ‘Governance Engine’ acting as a firewall for HR data, implementing a ‘Chaos Monkey’ to stress-test data integrity.

A rigorous audit of the Gender Pay Gap and Leadership Representation, uncovering a ’leaky pipeline’ despite achieving pay equity.

A deep-dive analysis challenging retention myths, revealing that ‘High Performers’ are 16% more likely to leave than average employees.

A Streamlit tool designed to restructure manager meetings, transforming unstructured chats into strategic career conversations.

A counter-intuitive analysis of the ‘Promotion Paradox’, revealing that high performers are 17% more likely to leave immediately after a promotion.