<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/ca702bac7bda429b971e80f5ada47df4&quot; frameborder=&quot;0&quot; width=&quot;1852&quot; height=&quot;1389&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1389</height><width>1852</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1389</thumbnail_height><thumbnail_width>1852</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/ca702bac7bda429b971e80f5ada47df4-884c0fd254fce7be.gif</thumbnail_url><duration>168.504</duration><title>Employee Attrition and Overtime Analysis: Insights and Strategies</title><description>Hello, my name is Saule, and in this video, I share my solo hackathon project focused on analyzing employee attrition and overtime. I worked with real HR data from IBM to uncover insights on why employees leave companies and how turnover can be reduced. My findings indicate that employees who work overtime are more likely to leave, and factors like lower salaries and job satisfaction play significant roles. I also developed HR strategies based on these insights, which you can find in my GitHub repository. I encourage you to check out my work and consider how these strategies could be applied in your own organizations.</description></oembed>