2023: Interested in working as a data scientist?
2023: Interested in working as a data scientist?
2023: Interested in working as a data scientist? Here are the essential details.
2023: Interested in working as a data scientist? If so, you are not by yourself. However, the approximately 106,000 data scientists in the U.S. and those wishing to enter the industry — where the average wage is $100,274 per year — may be wondering what the following year will bring due to the quickly changing economic conditions and recent large layoffs at businesses like Meta. Which abilities will be in greatest demand? What actually happens throughout a data scientist's regular day? What are the most prominent market trends?
The numerous routes experts choose to enter the field and the specialized skills they acquire along the way can sometimes make data science appear more complicated than it actually is. For instance, 20% of students who intend to pursue a career in data science cite the lack of clarity regarding the experience that is truly necessary as one of the largest entry-level entrance obstacles in Anaconda's 2022 State of Data Science study. Additionally, individuals who are already employed in the sector claim that their duties range widely, from system administration to actual data science or engineering, cloud engineering, research, and even instruction.
3 significant false beliefs regarding data scientists
Liu has noticed three main misconceptions about the field in her work and from her podcast talks:
1. Everyone regards you as a math prodigy.
According to Liu, people believe you need to know a lot of arithmetic or have a doctorate. But in reality, she said, you don't have to calculate everything because of programs like Python or various data science packages. Despite this, "I think everyone can learn the foundation, and you definitely need to comprehend it."
Liu continued, "I don't think I'm a math genius," Throughout reality, she admitted, "I battled a lot in my undergrad degree." Overall, no one is "cut out" to be a data scientist, she continued. I've failed, I don't think I was "cut out" to be a data scientist, she stated. "Everyone has struggled and is still trying to make sense of things. We're all still attempting to look for solutions on Google or Stack Overflow.
2. Data science is similar to magic.
People sometimes claim that what we do is somehow magical, but in truth, Liu said, "We often just spend time with the data." You want to start with something simple and build on top of data so you can understand how your solutions function, which some people refer to as "being one with the data."
And sometimes the greatest way to perform data science, she continued, is to make things straightforward and uncomplicated. "Sometimes the straightforward solution works better," she remarked. "I'd rather recruit someone with solid fundamentals than someone who always talks about those advanced skills but doesn't actually understand what they entail."
3. The only method of communication is through intense technical problem-solving.
Liu emphasized that data science is more than just technical expertise. Soft talents like empathy and understanding are frequently important.
In addition to analyzing the data thoroughly and developing models, we also consult with the company's product managers, according to Liu. Because your data science or insights will eventually change people's behavior or business elements, you need to develop empathy for your stakeholders. People need to be informed, and you must explain things.
What kind of jobs in data science can we expect in 2023?
The future of the data science profession is questionable due to concerns about an impending recession and additional layoffs. However, Liu asserts that certain essential technical abilities and character attributes will endure difficult times.
These include an emphasis on generating ROI to resolve business issues, the capacity to communicate model results to stakeholders, and the importance of empathizing with end users while resolving issues.
Even for machine learning, Liu stated, "You need to think like a business owner." "You may have a lot of really technical abilities and an understanding of the models, but you also need to just think because you want to solve a business problem," the speaker said.
She has already seen a rise in the amount of diversity in the sector, both in terms of gender and color.
Although Anaconda's research indicates that in 2022, the data science profession will still be 76% male, 23% female, and 2% non-binary, Liu is certain that this will change despite the statistics.
Don't wait until you see more people who resemble you to take action, she advised. Maybe there aren't many individuals that resemble you, but perhaps it serves as more of an incentive for you to become one and serve as a model so that others can see you and be inspired.
The most important piece of counsel from Liu had absolutely nothing to do with data science: "Find a balance between finding value for the business and also having a fulfilled, balanced life for yourself."
The tech sector is undergoing a major shift, and layoffs are occurring at an alarming rate. As of mid-November, over 45,000 employees in the American tech sector had been let go from major companies like Netflix and Twitter, according to Layoffs. FYI. A cycle of aggressive expansions, corporate excess, and wild talent wars to acquire the best and brightest is discussed in a New York Times story. Some of the reasons given for the continued layoffs include a rapidly growing headcount, fast expansion over profits, and getting caught in a tech bubble.
Sadly, the constant stream of layoff news coincides with the global economic unrest brought on by a pandemic. a generation has lived through a number of them.
But how can companies, particularly in the tech industry, get ready for such unsure times and smaller workforces? Are there investments or upgrades that businesses may make with the development of technology to withstand the impending storm of uncertainty?
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