How Long Does It Take To Become A Human Resource – Glassdoor has placed Data Scientists in the top 3 on its “Best Work in America” list for 5 years in a row. But how long does it take to become a data scientist?
Many are familiar with the 2012 Harvard Business Review article titled “Sexiest Work in America” as a Data Scientist, but some may wonder if the appeal is continuing. Demand is definitely ongoing – Glassdoor has ranked data scientists in the top 3 on its “Best Work in America” list for 5 years in a row.
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This should come as no surprise to anyone who is aware of data trends. The exponential growth in data-driven decision-making, combined with the emergence of low-cost and high-performance computing systems, has made the demand for data scientists even greater than expected in 2012 by HBR, leading to a shortage of data specialists.
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While the demand for data analysts is high and the salary is rather high, the median starting salary of a data scientist is $ 114,528 according to Glassdoor. If you’re wondering, “How long will it take me to become a data scientist?” The answer is that it may not take as long as you think.
Data analysts are a very diverse group of people and their skills will vary by job title. That said, there are some universal skills that any data scientist should master.
What is data science? It is an interdisciplinary field that analyzes data to solve problems and make business decisions.
The primary job of a data scientist is to extract real-world input, apply scientific methods, processes, algorithms, and computational systems, and then extract knowledge and insights. The ability to develop machine learning models and predictive models is one of the main things that set data scientists apart from data analysts.
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There are many data science programming languages, and most data scientists will be proficient in several. Some of the more popular development tools include:
If a data scientist is to find meaningful insight into the problems and capabilities of his business, he needs mathematical skills. The latter is what it takes to turn real scenarios into solvable problems. Mathematics will play a key role not only in asking questions that can be answered, but also in interpreting the results that algorithms give you.
You don’t have to be a math professor to be a data scientist. You just need a solid foundation in the following areas:
Data analysts can break numbers and IT professionals can code, but driving technical skills to solve business problems is what sets data analysts apart.
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To evaluate a business scenario and develop a data model that delivers practical insights, working knowledge of business intelligence (BI) is a skill that every data scientist needs. For this reason, some data science curricula may include several business or financial classes to provide a framework for running a business.
Since a data specialist works with business professionals who know much less than they do about coding and statistics, being able to explain your ideas is essential.
From writing reports to presentations, a data scientist must be able to convey his insights in a way that non-technical professionals can understand. This includes using data visualization tools like Tableau to bring your data to life. Regardless of the method, be ready to communicate with people who are not experienced in data science.
While most data scientists have at least a master’s degree, 25% only have a bachelor’s degree. Some data managers learn that you may not need a degree in that particular field at all. Some companies are delighted to welcome data scientists who have come from data science bootcamps.
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“Many universities offer bachelor’s degrees in computer science, but it takes an average of four years to obtain one. And, depending on the college you choose, you can spend up to $ 99,000 on a four-year degree where you can complete a science course for less than $ 20,000.
As most data science roles require a master’s degree or higher, further education may be necessary. Some graduate programs can be completed online in as little as one year. And the longer you stay in school, the more you’ll have to pay – although financial aid may be available.
Since going to university is too long and self-study is not always perceived as justified, an intermediate route is often sought. This is what data science training courses do. Through intensive and job-specific training from industry-leading experts, students enrolled in data science training courses gain an engaging and hands-on experience in data science – without the unnecessary courses required by universities.
This data-oriented approach enables students to assimilate the information they need while drastically reducing travel time and costs. For example, Flatiron School offers full-time data science programs that can be completed in as little as 15 weeks, and the flexible pace option can be completed in 20, 40, or 60 weeks.
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By the time they finish, they have a series of networks to get career support and even career coaching. The only downside is that some data managers prefer a formal college degree.
Many data scientists already have the math, business, and communication skills to become a data scientist – just add coding knowledge. If you have sufficient entry requirements and some degree – ideally in the STEM field – self-study and a few programming proficiency certifications may be enough to enter the data science industry. Try a free lesson at Flatiron School to see if you’re ready to jump in.
Self-study may be the cheapest, but requires sufficient discipline to stay on task and is not for everyone. And it’s harder to prove what you know and how. It’s also important to make sure you’re learning the right material from legal sources, otherwise you may feel less endowed than you thought – which is why some data science positions may not consider self-study appropriate.
Since there are so many different paths to get there, the time it takes to become a data scientist can vary.
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Those who follow the university path can become a data scientist within 3-4 years. For 75% of those who choose to pursue a master’s degree in data science, it may take an additional 1-2 years.
The total time can be raised to 5-6 years. While self-study may be the shortest path, it is largely up to the learner. Committed students can complete their studies in a few months, while those who get distracted can extend their journey indefinitely.
Data science training courses can help students achieve their goal of becoming a data scientist in just a few months. Some initial bootcamps last around six months – but most take around 12-15 weeks. The bootcamp path may be the fastest option for some to become a data scientist
If that sounds interesting to you, start your journey to becoming a data scientist at Flatiron School today.
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Flatiron School offers an immersive online data science program that you can complete in just 15 weeks. Schedule a 10-minute party chat to learn more.
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