Tdwi: Navigating Your Data Science Career
From undergraduate to working professional, these four milestones create a guide to a career in data science.
Data science is an ever-changing profession with rapid expansion across a multitude of industries and specializations. This growth can make entering the industry and finding the right career path challenging. Fortunately, there are numerous resources and opportunities to assist in navigating a data science career.
This article will focus on four key career milestones that can provide direction in your data science career journey. These milestones include preparing to enter the market, finding analytics passions, diversifying experience, and bridging business specializations.
Preparing to Enter the Data Science Market
In college many people assume that internships are the only path to gaining experience needed for finding a first job. Although internships are one of the best ways to gain experience and build a résumé, there are many other opportunities.
For example, co-op programs are a great resource for getting into the data science market. These programs tend to be full time, paid positions during a college semester that give hands-on company experience.
Another lesser-known opportunity that has grown for data science students is Research Experiences for Undergraduates (REU). This program supports active research participation by undergraduate students in any of the areas of research funded by the National Science Foundation. Students do not have to be enrolled at the university that is offering the REU, so many opportunities are available across the country.
Additionally, there are several websites and universities that offer online training and certifications that allow a student to gain knowledge on a data science specialty and add that achievement to their résumé. As a bonus, some of these courses are offered for free by universities such as Stanford and Johns Hopkins (through Coursera). Having any of these experiences on your data scientist’s résumé can help set you apart from your data-scientist-to-be peers.
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