Most data science newbies are confused about the types of data science projects they should have on a resume. So if you are one of those people who want to know how to work on data science projects for your resume, this article is for you. In this article, I’m going to walk you through an amazing strategy you should follow to work on data science projects for your resume.
How to Work on Data Science Projects for Resume?
When creating your resume as a Data Scientist, you must first be clear about your interests and the domain in which you want to work as a Data Scientist. If you are not clear about your interests and what domain you want to work in, it is very difficult for you to even get the job you want.
By interests and domain, I mean you need to be clear about what type of business you want to work for as a Data Scientist. For example, I am from a commerce background, so I have enough knowledge in finance, marketing and business. Of these, marketing is what interests me the most, so I think as a Data Scientist, I can add a lot of value to marketing a business or working for a business that is focused on advertising the products of other companies (for example, media.net, Google, Facebook).
So you need to be clear enough about the area of expertise so that you can work in a business where you can add the most value for its growth. Then you should work on data science projects related to your domain knowledge. For example, I like working on computer vision applications but I’m very interested in the marketing domain. So if I go for an interview for a Data Science job in Marketing with projects related to computer vision in my resume, it will be very difficult for me to explain how I can add value to their business. So if you have a clear idea of what area you want to work in, then you should only work on projects related to that area.
Types of Projects You Should Have in a Data Science Resume
Now the next important thing that you need to understand is what types of projects you need to work on for your data science resume. Choose topics to work on projects that are not very common among data science newbies. Find data science professionals on LinkedIn who are already working in the field you are interested in, then search for their projects on LinkedIn, Github, and Kaggle.
You don’t need to be working on the same types of projects if they were done years ago. Just look at the topics and find other related business problems based on today’s competition and technology. For example, in marketing there is a concept of customer segmentation, it is very important to market a company’s products to the most interested customers. If I did this project 3 or 4 years ago, it may have easily impressed my interviewer. But today this problem is very common among the data science community, it can still impress interviewers but depending on today’s business issues, I will choose to work on projects like customer personality analysis and Online Shopping Intent Analysis for my Data Science Resume regarding the Marketing domain.
So this is how you can also choose what types of projects to work on for your data science CV. You can find some of the best projects for your data science resume solved and explained using Python from here. Be clear about the domain in which you want to work as a data scientist and then work on data science projects related to that domain. I hope you liked this article on Data Science projects for your CV. Feel free to ask your valuable questions in the comments section below.