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The Amount of Time Spent Actually Working: Perspectives from Data Professionals

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One of the ongoing debates in any field, including data science, revolves around the actual number of hours spent working per week. A recent Reddit thread dove into this subject, with professionals offering their unique insights and experiences. While some people reported a traditional 35-45 hours, a significant portion revealed they worked far less, hinting at a potential shift in work norms in the field.

The Perceptions

The original poster (OP) initiated the discussion by explaining their experience in two different roles at Fortune 500 companies. At their first job, the workload was about 20-30 hours per week. However, their current role sees them working just around 8-10 hours. The OP expressed that their role, even though it is in data science, simply doesn't have enough work to keep them busy for the conventional 40-hour week.

Many Redditors resonated with the OP’s experience, including a user who shared a rather tongue-in-cheek comment: they only do about fifteen minutes of actual work in a given week. Another user admitted to focusing on their work for only 2-4 hours, while the rest of the time is dedicated to meetings, chatting, planning, organizing, and documenting.

The Hours

The distribution of work hours varied significantly among the Reddit users, with many emphasizing that their numbers represented "actual work":

  • About 20% of the users indicated they worked the standard 35-45 hours per week.
  • Nearly 30% revealed that they spent 20-30 hours per week on their tasks.
  • Around 40% reported working less than 20 hours per week, matching the OP's experience.
  • A small 10% of respondents admitted to working more than 45 hours per week, indicating they may have roles with larger scopes or more responsibilities.

The Takeaway

The thread illustrated that work-life balance has become a more significant factor for data science professionals, especially those who have the flexibility to work from home. Despite the conventional 40-hour workweek, many professionals in data science seem to be working significantly less. While this might seem concerning, it’s important to note that several factors can contribute to this disparity, including the nature of the tasks, efficiency levels, and automation capabilities.

It's also crucial to note that while these Reddit users represent a valuable snapshot of the data science field, they do not capture the entire picture. Nonetheless, the conversation suggests an evolving landscape, with a decrease in 'actual work' hours becoming more common.

To conclude, whether you're clocking in 40 hours or merely 10, the key is whether you are generating value for your employer to justify your pay-check.