Reprinted from: https://towardsdatascience.com/how-to-build-a-data-science-portfolio-5f566517c79c
1. How can I find a job about Data Science?
- Required skills: statistics, machine learning, programming ...
- Having a portfolio of public evidence of your data science skills.
- Experience. '' Projects are perhaps the best substitutes for work experience.''
- Keep on learning from your interviewing experiences
2. How to make a resume?
- Length: Keep it simple and one page max. This gives you the most impact for a quick skim. Recommends a simple one column resume as it is easy to skim.
- Objective: Don’t include one. They don’t help you distinguish yourself from other people. They take away space from the more important things (skills, projects, experience etc). Cover letters are extremely optional unless you really personalize it.
- Coursework: Do list relevant coursework that is applicable for the job description.
- Skills: Don’t give numerical ratings for your skills. If you want to rate yourself on your skills, use words like proficient or familiar or things like that. You can even exclude assessments altogether. Do list technical skills that the job description mentions. The order you list your skills in can suggest what you are best at.
- Projects: Don’t list common projects or homework. They aren’t that helpful in distinguishing you from other applicants. List projects that are novel. Show results and include links. If you participated in Kaggle competition, put percentile rank as it helps the person reading your resume understand where you are in the competition. In projects sections, there is always room for links to writeups and papers as they let the hiring manager or recruiter dig in deeper (bias to real world messy problems where you learn something new).
- Portfolio: Fill our your online presence. The most basic is a LinkedIn profile. It is kind of like an extended resume. Github and Kaggle profiles can help show off your work. Fill out each profile and include links to other sites. Fill out descriptions for your GitHub respositories. Include links to your knowledge sharing profiles/blog (medium, quora). Data science specificially is about knowledge sharing and communicating what the data means to other people. You don’t have to do all of them, but pick a few and do it.
- Experience: Tailor your experience towards the job. Experience is the core of your resume, but if you don’t have work experience what do you do? Focus your resume on independent projects, like capstone projects, independent research, thesis work, or Kaggle competitions. These are substitutes for work experience if you don’t have work experience to put on your resume. Avoid putting irrelevant experience on your resume.
