Therefore, in-depth domain knowledge of the customer is required for a data scientist to gain better results. However, he cautions new entrants to the field to go into it with their eyes open. This guide would set a framework that can help you learn data science through this difficult and intimidating period. For an engineering and IT professional, transitioning into a data science role that deals with a forecast of customer sales might prove difficult. "Companies are increasingly using the data scientist title for other similar roles such as data analyst or statistician," said Zhao. After all, ‘data science’ still isn’t really something you learn in school, though more and more schools are offering data science programs. Showcase your skills to recruiters and get your dream data science job. Data Science, therefore, is practice-heavy and requires the right approach to solve its problems. Data Science – Is it Difficult to Learn? This is one of the main reasons as to why most proficient data science professionals hold a PhD in quantitative fields like finance, natural sciences, and statistics. For several years data scientist has been ranked as one of the top jobs in the US, in terms of pay, job demand, and satisfaction. The data science projects are divided … You must know the importance of Hadoop for Data Science. before knowing the difficulty of data science, you must first know the exact purpose of Data Science. Â, Keeping you updated with latest technology trends, Join DataFlair on Telegram, Almost everyone wants to become a Data Scientist these days without knowing the difficulty that lies ahead in learning data science as well as implementing it. Artificial Intelligence In the present, is mind-boggling and viable however no place close to human knowledge. discuss how data science is difficult and some of the problems that are faced by data scientists as well as data science aspirants alike. This means that data science teams that work in isolation will struggle to provide value! As for the reason for the salary squeeze, for Glassdoor's Zhao, it's clear that there are now more candidates for data scientist roles than there are jobs available. No, data science is not easy. But there are signs the coveted role may be losing some of its sheen, as salaries for data scientists begin to plateau. Data Science roots from multiple disciplines. "The past ten years have been a bit of the Wild West when it comes to data science. Glassdoor's Zhao is also quick to point out there are still many aspects of being a data scientist that make it an attractive role -- not least the fact that US data scientists are still taking home $95,459 in median annual pay. Transitions into data science are tough, even scary! A Data Scientist is required to find patterns within the data and generate insights by taking conclusions from the data. Even the most … But, the volume of data is growing at a pace that seems to be hard to control. While these skills are necessary for building the fundamentals, it is the domain knowledge that brings data science into the picture. ', it's been a really open question. Data science is an emerging field, and those with the right data scientist skills are doing. Is it still worth becoming a data scientist? It requires people who are inquisitive enough to persevere through the toughest of problems. With slowing salary growth among data scientists and signs there may be a glut of junior talent, should aspiring data scientists pause for thought? There are then several sub-constituents of these disciplines that a data scientist must master. For example, in order to become proficient in programming, a programmer spends years to master his domain. "As data science has risen in prominence, enrolments in data science programs and bootcamps have exploded. Hadoop, Data Science, Statistics & others. Data Science is a blend of various tools, algorithms, and machine learning principles with the goal to discover hidden patterns from the raw data. "It can be very hard for someone with a new degree in data science to find a data science position, given how many new people they're competing with in the market," she wrote. With salaries flattening and competition rising, there are signs the prospects for data scientists may be less stellar than once thought. Data Science is math heavy, and many people who are data science aspirants would want to have a grasp over the core mathematical concepts before venturing in the field of data science. Wait! This includes recording, storing and analyzing data. Since, data science is a recent field, finding experienced candidates is one of the toughest problems … Data science interviews are still very hard to get right, and still a complete mismatch for jobs. I am a college drop out (I start with that because apparently if you don’t come out of the womb with a phd in theoretical physics and 15 years of data science experience something must have gone wrong with the birth). By adding data analytics into the mix, we can turn those … through careful analysis and assertion. Hope you enjoyed reading the article. For example, a person pursuing a PhD in biostatistics is required to hold command over a programming language like R to implement statistical models for generating findings. It’s really important to clarify these questions because many articles on the topic imply that a data science career is an easy way to become rich, happy and smart for good. TechRepublic Premium: The best IT policies, templates, and tools, for today and tomorrow. © 2020 ZDNET, A RED VENTURES COMPANY. It still lacks a proper development base and is more of an umbrella form. So whether it's structured or unstructured, data scientists use scientific methods, statistics, processes and algorithms to gain insight into data… According to the Bureau of Labor Statistics, career opportunities in this field are anticipated to grow … SEE: Feature comparison: Data analytics software, and services (Tech Pro Research). This further makes data science a difficult challenge for many industries. Starting and navigating through the data science career can become a daunting challenge for beginners due to the abundance of resources. Furthermore, data scientists need data to make better products for their customers through careful analysis and assertion. Data Science is a complicated field, especially for those who have no prior experience in this field. "There might be a skills shortage, but not an applicant shortage. One confounding factor to bear in mind, however, is that comparing salary figures for data scientists over time is made difficult by how poorly defined the data scientist role is. It’s a combination of hard skills (like learning Python and SQL) and soft skills (like business skills or communication skills) and more. There you will find 370+  FREE Data Science tutorials that can help you to become a master of it. Data is the lifeline of a Data Scientist. Fields like mathematics, statistics, programming are some of the key disciplines that make up data science. Time and time again, industry data, market trends, and insights from top business leaders highlight soft… The domain knowledge comes from experience. Since, data science is a recent field, finding experienced candidates is one of the toughest problems faced by several companies. Top 5 programming languages for data scientists to learn, 7 data science certifications to boost your resume and salary, Feature comparison: Data analytics software, and services, analyst reports often discuss the sharp uptick in demand for data science skills, a fivefold increase in the numbers applying for junior data science roles, reports of a data science skills shortage, to consider getting into the field by the "back door", not least the fact that US data scientists are still taking home $95,459 in median annual pay, How to become a data scientist: A cheat sheet, 60 ways to get the most value from your big data initiatives (free PDF), Volume, velocity, and variety: Understanding the three V's of big data. There are many new university degrees and boot camps for data science that have started to address this problem through imparting structured knowledge to the students. Therefore, it becomes a challenge for the data scientist to be specialized in multiple roles. This is because of the massive skill gap that is contributed by the major difficulties that plague the field of data science. To get in-depth knowledge on Data Science, you can enroll for live Data Science Certification Training by Edureka with 24/7 support and lifetime access. "Data scientist salaries are moving closer to the mainstream of software developer salaries in general," said Stack Overflow data scientist Julia Silge, adding there was "much less of a difference" between the pay of the two groups when controlling for education level. Figures produced by Glassdoor Economic Research show a year-on-year fall in US data scientist wages in February and March of this year. Zhao says it's important to understand that while businesses may be struggling to find the skills they need, that doesn't mean there's not enough entry-level talent. Big data has been driving technological innovation and scientific discovery all around the world. In the end, we conclude that data science is a highly difficult field that has a steep learning curve. When employers talk about shortages, they're generally talking about a lack of experienced professionals," he said, adding this largely stemmed from the newness of data science as a mainstream field. And from there, extracting useful information. ALL RIGHTS RESERVED. Also, at the end of this blog, I am providing you the best guide to learn Data Science quickly.Â. Various industries make use of data science. "When you get to that stage it becomes easier to hire for those roles, and when these roles are easier to hire for you don't have the crazy salary situation we had before.". they must thoroughly understand the problems and apply an analytical approach to solve them. People with just a few days of training will have a hard time getting a job. Data science jobs easy to find, tough to fill 4 Data scientist ranks as the top job in America this year, as low supply and high demand mean big money for those who qualify for that emerging IT … This means that if you only grasp the theoretical knowledge and do not practice it, it will be easily forgotten. Data Science is a recent field. Non-Technical Skills. I am not in any way saying that the complex discipline known as data science is easy or that becoming a proper data scientist is simple. So, read the complete blog and you will find the answer. "I think that what we're seeing is a little bit of the standardization and the professionalization of data science," she said. One cannot become a proficient data scientist only through solving projects, participating in boot camps and acquiring knowledge from various online resources. These problems are focused on developing models that tackle some of the hardest business problems. 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