HR Analytics — Gaming Industry

Workforce planning & diversity KPIs for the gaming industry — portfolio case study using synthetic data.

Disclaimer: This is a portfolio project. All data is synthetic. Not affiliated with any company.

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Overview

An interactive Streamlit dashboard for HR analytics in the gaming industry — workforce planning, diversity KPIs, salary benchmarking, and attrition modeling.

Built as a portfolio case study to demonstrate applied HR analytics techniques using Python, SQL, and interactive visualization.

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Features

• 📊 Workforce dashboard — headcount trends, department breakdown, seniority distribution
• 🎯 Diversity KPIs — gender, seniority, and team composition tracking
• 💰 Salary analysis — compensation distribution by role and region
• 📉 Attrition modeling — churn risk scoring with feature importance (SHAP)
• 🔍 Interactive filters — by studio, role, region, and time period

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Repository structure

hr-analytics-gaming/
├── app.py                  # Main Streamlit application
├── src/
│   ├── data_loader.py      # Synthetic data generation
│   ├── kpi_engine.py       # KPI computation logic
│   └── viz.py              # Chart helpers (Plotly)
├── data/
│   └── synthetic/          # Auto-generated on first run
├── requirements.txt
└── README.md

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Getting started

git clone https://github.com/remichenouri/hr-analytics-gaming.git
cd hr-analytics-gaming
pip install -r requirements.txt
streamlit run app.py

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Tech stack

Python 3.9+ · Streamlit · pandas · Plotly · scikit-learn · SHAP · SQL

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Use cases

• HR analysts — tracking workforce diversity and compensation equity
• Data analysts — exploring HR analytics techniques on a realistic synthetic dataset
• Portfolio — demonstrates applied analytics in a domain-specific context

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Contact

Rémi Chenouri — Healthcare Data Analyst | Commercial Performance
📧 chenouri.remi@proton.me · LinkedIn

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Portfolio project — synthetic data only. Not affiliated with any gaming company.