5 Key Takeaways From Our Data Journalism Career Panel

2 November 2022

By Stella Min

The ADSA Career Development Network recently hosted a career panel to offer a glimpse into the field of data journalism. The panelists shared tips for finding and landing a job and some of the challenges and rewards that come with the work. Below are 5 key takeaways from the event.

ADSA Career Development Network career panel series on Data Journalism

Panelists from left to right and top to bottom: Sandeep Bansal - Data Scientist at Warner Bros. Discovery; Casey Miller - Full Stack Software Engineer at Locana; Sandhya Kambhampati - Data Reporter at the LA Times; Christine Zhang - Editing Resident at The New York Times Graphics Desk.

1. Winding Career Paths

The first key takeaway is that there are many different pathways into data journalism. Each of our panelists found their way into data journalism through a series of decisions that enabled them to explore and deepen their interests in different aspects of the work. For example, Casey Miller happened to take a class in multimedia as an undergrad at the University of North Carolina at Chapel Hill that sparked her passion for working with data applications. Christine Zhang and Sandeep Bansal, however, did not receive formal training in data journalism. Christine's interest grew from her exposure to data and graphics journalism while she worked at the Brookings Institution after earning a Master's degree in quantitative methods. To gain experience, she began seeking projects that would enable her to acquire the skills and develop a portfolio to break into the field. Sandeep's interest was sparked by his roommate who motivated him to pursue a master's degree and switch his career from healthcare to data science. The panelists' career histories demonstrate that there are multiple ways to enter the field of data journalism and that the pathway into the field may be nonlinear.

2. Trend Toward Specialization

The second takeaway is that the field of data journalism increasingly requires specialized skills. Given the rapid advancement of technology and methods, people entering the field today may need more specialized training than those who entered the field as little as 5 years ago. Technical skills that are high in demand include statistical methods, interactive visualization, and front- and back-end applications. Strategically specializing in high-demand skills like these can increase the likelihood of landing a desirable job.

3. Follow Your Interests

The third takeaway is to let your interests determine which skills you specialize in. The growing demand for technical skills in data journalism can lead you in many different directions, so it is important to take the time to explore and narrow in on the aspects of the work that truly excite you. Start by pursuing side projects that will enable you to practice collecting, manipulating, analyzing, and presenting data. This could be through formal training like taking a class online and earning a certification or informal projects like automating routine tasks in Python. Slowly but surely, by exploring your interests, you'll eventually discover what you like and dislike about the work that goes into data journalism. Once you have honed your interests, you'll have a better idea of the type of job that you may want to pursue.

4. Targeted Job Searches

The fourth takeaway is that the perfect job may not be posted on popular job websites. While websites like LinkedIn and Twitter are certainly a great place to start your search for jobs in data journalism, you should also check niche communities like OpenNews and News Nerdery which share unique opportunities that may not be posted anywhere else. If you are just starting your career, large media organizations regularly post internships directly on their website. Start to look into their internship application cycles so that you can prepare your application ahead of time. If job opportunities on traditional websites are unappealing, you can look for positions posted by companies sponsoring professional conferences of interest. This is how Casey landed her current position at Locana.

5. Flexibility

The fifth and final takeaway is that the day-to-day work of a data journalist can be highly variable, depending on your area of specialization. Certain technical skills, like the ability to create stunning data visualizations, can enhance news stories on many different topics, which means regularly covering unfamiliar subjects. The work is driven by current events and news cycles, which requires the ability to shift as stories evolve with new information.

Summary

Data journalism is a dynamic field that has seen tremendous changes in just the past five years and the growing demand for technical skills has pushed the need for greater specialization. However, there are many different ways that one can specialize. It is important to reflect on your interests along the way to ensure you are headed in a direction that is sustainable for your career. Internships are a great way to explore and get a head start, along with targeted job searches once you have begun to specialize. Regardless of the stage of your career, it is important to stay flexible, as news cycles change and drive data and graphics projects.

You can dive into all these tips and more by watching our Data Journalism Career Panel. Check out our previous panels to learn about other career paths for data scientists.

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