Aaron Reinke in  
Data Analyst  

Leap into Data Science

I'm an epidemiologist with four years of experience, deeply involved in data analysis tasks like survey creation, report generation, and developing data systems using GIS, Tableau, R, and Python. I'm contemplating a temporary shift from my current role to focus on my small business, not for financial gain, but as an opportunity to grow my data science skills. Unfortunately, there is no growth opportunity for data science at my current role, outside of me paving the way myself.

I plan to dedicate 4-6 months to hands-on projects including web scraping, market analysis of e-commerce data, and integrating Al and machine learning into my data analysis and data collection workflows. My hope is to apply Python, R, and web development skills to improve my technical expertise and become a better candidate for data scientist jobs. 

I plan to apply to the data science field after the brief growth period, but I'm curious about the community's thoughts on this approach. How is this career "gap" perceived? Are the skills that I listed above enough or is there something else I should include in my projects?

Insights or similar experiences from those who've taken a similar path would be incredibly valuable. Recommendations and advice is also welcomed. 

Note: I have enough money to take this time off without worrying about my savings for at least 10 months.
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DaftmindData Science Manager  
Your thought process is sound, for sure. A lot of people have had employment gaps recently due to layoffs and, interestingly enough, it almost seems like it's become expectation that you work on your skills or develop something in your time off, so you doing it proactively should reflect really well. I think based on your details above, the skills and tools you're aiming for should definitely be enough and get you into a good role. My suggestion would just be to ensure that you have the data and metrics to be able to talk on. When interviewing with tech, it's imperative that you're able to explain the cause and effect of a lot of your work and show the results.
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