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How To Create A Project Portfolio For Data Science Job Applications

In general, no company would recruit a candidate for a specific job-role in which the person has zero experience. You need to showcase that you have got the needed experience for the job role you are applying & in case, if you are a fresher, then your skills would be assessed based on the projects that you have previously handled at the time of your training period. The same concept gets applied for the hiring process in Data Science. Getting hired in the field of Data Science as a fresher would require the candidate to build a strong project based portfolio.

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Projects to Include in a Data Science Portfolio

As a fresher in Data Science, your project portfolio should consist of a minimum of 3-5 projects. You shouldn’t just pick some random projects to work & add them to your portfolio as it wouldn’t do you any good. You should be considering the following factors prior to selecting the project. 

  • Kinds Of Tasks

You should know what kind of tasks you are required to gain expertise in to get hired. Data Cleaning, Data Analysis, Machine Learning, Data visualization, Natural Language Processing, & knowledge of tools & several other techniques are considered as the basic requirement for hiring in Data Science.

  • Subject Areas

Know the areas where you are going to apply. For instance, if you are interested in going towards marketing industry then work on projects that are marketing-related. Pick the projects that are relevant to the industries in which you are interested to apply for a job.

  • Types Of Data Sets

The basic criteria to get started with any project in Data Science would be ‘data set’. Data may be common in different industries & so if you work on the project that involves the data set which is also used by the industry in which you are going to apply for the job, then this will surely be an added advantage.

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