Example: You built a model to predict who would cancel their subscription and introduced an intervention to improve monthly retention from 90% to 93%.Example: You developed a pricing algorithm that resulted in a $200k lift in annual revenue.Ways to define the impact of your data science work
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For example, did you automate a report? Roughly how many hours of manual work did you save each month? Here are some ideas for how you can quantitatively talk about your projects: You're a data scientist, so highlight your value by demonstrating the quantitative impact of your work. State the quantitative results of your project.You can mention the programming languages you used, the libraries, modeling techniques, data sources, etc.The template for successfully talking about your experience as a data scientist is: I want to see that "I'm wearing my favorite outfit" level of confidence. When talking about your previous work (whether that's for another employer or on a side project), your goal is to convince the person reviewing your resume that you'll provide value to their company. This is where the person reviewing your resume decides whether or not you'll get an interview. Let's jump right into the good stuff and talk about the most important part of your resume: your work experience and projects. Your data science projects and work experience Incorporate those specific projects into your resume. See if any projects you've worked on come to mind while reading it.
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