Remote opportunities are revolutionizing how we work. But is working from home an option for data scientists? Read on to find out.
Here’s what we’ll cover:
In March 2020, Mark Zuckerberg announced that thousands of Facebook’s employees would be going remote—for good. In an interview with The Verge, he predicted that nearly half of the company will work in permanently virtual positions within the decade.
The COVID-19 pandemic has only accelerated the shift toward remote work, particularly within the tech industry, where Indeed and Google employees will telecommute through summer 2021 (with the option to go remote indefinitely), and Twitter and Shopify employees will be able to stay remote for as long as they like. Other industries, from healthcare to finance, are also offering up a variety of work-from-home roles—many of which are in the field of data science.
Data scientists collect, manage, and analyze data to produce insights that help organizations make informed decisions.
Thanks in part to the advent of connected devices and the digital nature of products and services, companies are now inundated with massive amounts of data. This data has the potential to dramatically influence an organization’s growth and efficiency— but only if it is first converted into useful information. That’s where data scientists come in.
A data scientist’s work begins with data collection and management. They must acquire and clean data sets, which are then organized and stored using libraries and framework tools. Programming proficiency is necessary to wrangle data, maintain databases, and implement machine learning algorithms that analyze data.
Data scientists rely heavily on machine learning and statistical modeling to extract meaning from data. These tools enable data scientists to track trends, and identify patterns, causal relationships, and groups within vast data sets. After data has been analyzed, data scientists must interpret their results and present their findings in an applicable way to the rest of the organization.
Working from home offers a combination of rewards and challenges. In the wake COVID-19, data scientist Tom Sharp has been working remotely as data scientist for Deloitte, a top professional services firm. He has documented his experience in a post on Towards Data Science, and his observations provide a window into what working from home as a data scientist is really like.
Some upsides of remote work, according to Sharp, are obvious: no dress code, and an open workspace free of disruptions from clients or coworkers. But he has noticed some other upsides, too: working from home allows him to focus more on the technical aspects of data science as opposed to client interactions. Now, he spends the majority of his time producing visualizations, models, and analyses while other members of his team focus on client delivery.
Physical separation seems to have encouraged specialization within the team. This streamlined division of labor cuts down on time Sharp spends in non-essential meetings, which has improved his ability to focus and boosted his productivity.
Not all of the remote work-related challenges that Sharp has encountered are specific to the field of data science. Outside of an environment regulated by collective social rhythms of lunch hours and coffee breaks, he sometimes struggles to assess when to stop working. Even though he is more productive than ever, Sharp says that working from home has created internal pressure to constantly prove that he is working—he doesn’t want anyone to think he is taking advantage of decreased supervision.
Sharing ideas has also proven more difficult in a remote context. As a data scientist, Sharp relies heavily on informal visual aids in meetings. Instead of getting up in front of the group to physically illustrate a concept that isn’t coming across, Sharp now has to utilize alternative methods to convey his ideas. Virtual whiteboards have helped, but Tom has observed that they aren’t as effective as the real thing.
Many of the tools that enable remote work are already popular in office settings, according to Sharp. Telecommuting should not drastically affect the technical aspects of data science work, but data scientists will notice an increased reliance on collaborative applications.
Below are some of the tools data scientists rely on the most while working from home:
Using solid communication, collaboration, and time management strategies, data scientists can cultivate a successful work-from-home experience.
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