Advice for Students Looking for a Job in Data Science

Around mid-October, there is a rush of activity related to applications for graduate programs, internships, and full-time positions with companies. Over the years, I’ve acted as both a reviewer of student application packages and a reference or letter of recommendation writer. I’ve previously written in-length about the letters of recommendation policy I ask anyone seeking a reference to follow. However, I never expanded on the bigger picture of the application package: Personal Branding. In essence, how can you sell yourself as being a data scientist?

Generally, personal branding may be broken into multiple components. Some of these components are part of a traditional job search while others aren’t. I’ve opted to discuss briefly some branding strategies regarding: Resumes, Cover Letters, Personal Websites, Social Media, Professional Development Programs in Companies, and University Career Services.

Resumes and Curriculum Vitae (CV)

The most common requirement is a resume that documents your accomplishments to date. In academia, we have a tendency to want to see everything and, thus, we require a CV that is all encompassing and without a page limit. Now, this might seem daunting to create two; however, the R community recently show a very efficient and stylish way to create a resume/CV using RMarkdown to render in either HTML, PDF, or Word.

Consider basing the Resume/CV off of this design: https://livefreeordichotomize.com/2019/09/04/building_a_data_driven_cv_with_r/

Inside the resume or CV, make sure to provide a link to each project that you have mentioned if they are public. These projects will showcase your skills and abilities to recruiters. Bonus points if the projects can be used easily.

Cover Letters

When applying for jobs, you may be asked to create a cover letter that requires a few paragraphs on why you want the job. Many cover letters will have similar prompts. Try to create generic responses that can be reused with company specific details substituted in. This will cut down on the more time consuming parts of the application process.

Consider making the cover letter using:

• linl package; or
• Parameterized RMarkdown templates

Personal Website and/or Portfolio

Many students overlook the benefits of creating website, blog, or online portfolio. But, this is generally one of the most important aspects as many recruiters will search who you are. One quote comes to mind to emphasize this phenomenon…

“If it isn’t on Google, it doesn’t exist.” — Jimmy Wales (Wikipedia founder)

Do not mistake LinkedIn for a personal website. The cost to create a website is as low as purchasing a domain name, e.g. thecoatlessprofessor.com costs ~$12 per year. Hosting can be done for free with static websites through:

• Google Sites: Point and click website design.
• Netlify: Continuous Deployment (CD) of website source found on GitHub
• GitHub Pages: Deploy directly with GitHub to username.github.io

For help making a site using R, consider using blogdown. The blogdown package provides an interface to both hugo and jekyll that allows for content to be written with RMarkdown.

Social Media

First and foremost, make sure to sanitize the public profile view from college debaucheries. Part of this can be handled by changing visibility settings from
public (default) to private or “connections-only”. Moreover, consider creating two accounts – one personal and one professional – to obtain a better work-life balance.

If pursuing a career in Statistics, Data Science, or Analytics, please consider having a profile on:

• Twitter with tweets directed on #rstats or #python.
  • Share code snippets using https://carbon.now.sh/ or linking out to a personal website.
• GitHub to showcase using version control with analysis or development projects.
  • Create a README file that contains a high-level overview of the project along with instructions on how to obtain/use the material.
• Kaggle for feature mining and creating analytics pipelines.
  • Work on showing modeling workflows through kernels and rank competitively on project leaderboards.
• LinkedIn provides direct contact with most recruiters, professional society emails, and aggregation of special topics.
  • Try to draw out professional development opportunities and leverage the connection available within your network.

Professional Development Programs

Consider applying to a development program that will seek to provide a guided internship to full-time status program. Good keywords to search for are: “co-op opportunities”, “training development”, rotational programs”, “development program”, “fellowship training program.”

Sample search for Champaign and a few results…

Company-directed training programs:

• John Deere: Development Program
• Caterpillar: Analytics Professional Development Program
• Johnson and Johnson: Co-Op Opportunities

Fellowship Training Camps:

• Insight Fellows: PhD (req. Data Science) and MSc opportunities.
• The Data Incubator: MSc and PhD-level students.

Career Services

When in doubt, go to the advisors who are paid to make sure you secure a job post-graduation. The advisors should be able to verify the tone of the material. Potentially, the advisors might also point out job opportunities that match with your goals. At UIUC, there are a few different divisions related to career services:

• Engineering Career Services: Provides a bit better resources though requires being in engineering or in a CS + X program.
• The Career Center: Campus-wide career center for all majors.
• Department of Statistics Career Advising: Resources specific to Statistics majors.

Fin

Hopefully, these tips were helpful. As time goes on, I’ll try to add on a few more tips.