Getting your first data science job can be intimidating and tiresome. Getting a job is not always an easy task. You may have to apply to a large number to companies before you get a job. Here are some ways to help you in keeping you better prepared for the job and impress recruiters.
Make sure you are strong in the knowledge of the field. You must know the basic mathematical concepts of data science like statistics, multivariable calculus and probability. The main programming languages for data scientists are R and Python. SQL, Java, and MATLAB are also frequently used.
Tailor your Portfolio/CV
Bring to light your skills and projects. The number of significant projects you do can cover up for your lack of experience. Prepare a cover letter. You can explain more about your projects in the cover letter. Customize it for each data science job that you apply to.
Connections can help in many ways. You can let people know that you are looking for a data science job and they can share with the people they know and so on. Connecting to professionals in the field can aid in you finding a mentor. A mentor can help in recommending you for a job and helping you in your career path. LinkedIn is the professional network to make connections but you can try other methods and platforms also.
Make sure you have the skills
Technical skills like Excel and programming and soft skills like effective communication, quantitative analysis, creativity, strong business acumen, and curiosity are must-have skills for a data scientist. Practice analyzing data and articulately communicating your thoughts on it.
Starting a blog is a great way to do so. You must also practice visualization skills. Always be willing to learn new things. Technology is evolving every day. The field of data science will evolve too. There will be new tools and techniques that you must keep yourself updated on.
Show your code
Posting your projects and code in your GitHub account can help you showcase your skills. Your blog can go hand-in-hand with your codes. You can also have a Kaggle profile. As mentioned above, knowing coding languages like Python and R are essential for data scientists.