<![CDATA[The massive shift in work patterns caused by the global pandemic has significantly accelerated the adoption of remote work schemes across various industries and organizations. This condition has created a strong need for data-driven studies to understand the factors that influence employee productivity in flexible work environments. This study aims to analyze the relationships among several key variables, namely employment type (in-office or remote), weekly working hours, and well-being score, in relation to individual productivity scores. The research data were obtained from a publicly available dataset on the Kaggle platform, containing 1,000 entries from respondents with diverse professional backgrounds. The analysis process involved data preprocessing, Pearson correlation analysis, and exploratory data visualization using heatmaps and scatter plots to facilitate result interpretation. The results show that remote work is positively correlated with productivity (r = 0.40), while weekly working hours exhibit a negative correlation (r = -0.25). Meanwhile, the well-being score demonstrates a weak but positive correlation with productivity (r = 0.14). The data visualizations support these numerical findings by presenting consistent patterns among the analyzed variables. These findings offer preliminary insights that are valuable for future studies related to remote work productivity. This study can serve as an initial reference for decision-makers in designing data-driven policies to optimize flexible work arrangements.]]>
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