Data scientists use some of the most cutting edge tools in tech, and also reel in impressive salaries. So it’s no surprise that it takes some specialized training to be successful.
Since it’s such a new field, there’s no clear-cut path to getting hired in big data. So we’ve outlined some of the skills you need to learn as well as your course options to help you start your new career.
A Brief History of Data Science
Data science was first used as a tool to detect banking fraud but has now penetrated many different sectors. In 2008 several large tech companies realized the need for professionals with the ability to gather and analyze data. The term data scientist came into existence shortly after.
Hal Karen, chief economist at Google and UC Berkeley professor had forecasted in an article, published by McKinsey in 2009, that the most in-demand skillset for the next decade would be the ability to analyze data and extract value from it.
This prediction was spot on. According to Glassdoor, data science has been the number one job in the US for four years in a row. There’s an upsurge in demand for data scientists, and it’s not going to decline soon. According to the US Bureau of Labor Statistics, the demand for data scientists will see a growth of 27.6 percent in employment by 2026.
As the demand continues to soar there’s a dire shortage of data professionals. US companies spend megabucks on data science training, yet, it's still not adequate to meet the influx of demand.
What is Data Science?
Data scientists collect, store, organize and analyze data to help organizations to make data-driven decisions.
One of the most prominent examples of data science in action can be seen at Amazon.com. Amazon collects massive amounts of data and customizes its homepage depending on your recent purchases, search history, and buying behavior. These data-driven customizations can significantly boost sales and give Amazon an edge over its competitors. McKinsey Global has suggested that companies can enhance their profit margins by 60% through big data.
Data science doesn’t just benefit companies. By browsing custom products that are super relevant, consumers can save time and have a better online shopping experience. Companies like BlueDot are going one step further as they try to tackle the current pandemic. They’re analyzing high volumes of data to predict the next breakout and actually save lives with data science.
What Does a Data Scientist Do?
Data scientists are highly qualified professionals that possess strong technical knowledge. They build complex algorithms that organize and synthesize large amounts of data. The goal of a data scientist is to help drive business strategy through data-driven decision making.
Why Become a Data Scientist?
The demand for data science professionals continues to surge. Companies across the U.S. are struggling to fill their data-related positions. It’s not only the technology industry either. Various other job sectors also require data experts. In fact, big tech companies such as Google, Microsoft, Amazon, Apple, and Facebook employ only 1% of the workforce.
With such high demand comes lucrative compensation packages. According to Glassdoor, the average income of a data science expert in the U.S. is $113,000.
How to Become a Data Scientist
Now that you’ve decided to pursue a career in data science, you’re probably wondering how to get started. There are a few different paths you can take to learn the skills you need. Let’s discuss the options:
- Get a Degree: Earning a data science degree through a college or university is one way to acquire extensive knowledge and data science skills. You’ll have to apply to colleges and attend a fully-fledged graduate program. This route is great if you have sufficient time and money. Degree programs can cost up to $30,000 per year and take 4 years to complete.
- Enroll in a Bootcamp: Online bootcamps are certified intensive learning programs designed to teach you career-ready skills, fast. Sign-up to our data science bootcamp to benefit from one-on-one mentoring, community support, and professional guidance. We’ll stick with you throughout your learning and beyond to ensure you secure a data science position at a top firm. Our program of classes has been put together by data experts to cover all the topics you’ll need. Feel free to schedule a chat with admissions to learn more.
- Learn on the Job: If you have the opportunity to learn data science skills in your existing job, it can be a great way to get your foot in the door. It’s a solid option, provided you have a good mentor and a conducive learning environment.
- Teach Yourself: Learning by yourself is one of the toughest options to get started. Although there are several books that you can study and plenty of free online tutorials to watch, you’ll probably wind up confused about where to start and how to begin. Without a teacher or a role model, learning data science can be an arduous task that’ll test your perseverance. Most employers prefer certification from a recognized educational body. You’ll obviously have no formal recognition when self-teaching so it could make your job search more difficult.
Data Science Training
Data science is a mix of multiple disciplines like mathematics, statistics, and programming. To become an expert in any of these fields is one thing, but to master them all requires hard work and determination. Let’s look at some of the required skills in more detail:
- Coding: Data scientists transform unorganized raw data into something more useful with the help of programming languages. Python is one of the most popular languages used in the field. It consists of countless libraries for data visualization, natural language processing, and deep learning. R is another language specifically designed for data science. The majority of data scientists prefer using R to solve statistical problems.
- Machine Learning and AI: Machine learning is concerned with building computer programs that improve automatically and actually learn from their experience. It comes under the wider umbrella of artificial intelligence (AI), which involves designing computers that can think for themselves. To stand out in machine learning you’ll need to study decision trees, linear regression, logistic regression, regularization, K-means algorithm, and recommender systems.
- Data Visualization: To communicate discoveries to company stakeholders data scientists need to master data visualization. It helps organizations grasp insights quickly, thus allowing them to take faster decisions. As a data scientist, you must have a strong understanding of data visualization tools such as ggplot, d3.js, Tableau, Power BI, and Matplottlib. Python and R also have good data visualization libraries.
- Big Data Frameworks: As datasets increase in size, there’s a growing requirement to maintain efficiency. It’s expensive to change existing infrastructure. What’s not expensive is adding more machines to solve parts of a problem simultaneously. This is where Hadoop and Apache Spark come into play. A study carried out by crowd flower found that Hadoop was the second-highest ranked skill for a data scientist. It’s also valuable for data scientists to understand cloud computing such as Amazon Web Services, IBM Cloud, Google Cloud Platform, and Microsoft Azure.
Considering these challenges, it’s better to learn data science in a structured environment with the help of experienced mentors.
Is a Data Science Training Bootcamp Worth It?
Bootcamps equip you with all the skills you need for an entry-level or a junior scientist job. You’ll gain career-ready skills in the following areas: programming languages, data analysis, data visualization, data prediction, statistical analysis, predictive analysis, and Big Data frameworks like Hadoop and Spark. Here are several benefits to completing a bootcamp course:
- Bootcamps are flexible, they can be online, part-time, and self-paced. Even if you’re in full-time employment you can still attend them.
- Most bootcamps provide one-on-one mentorship programs to assist you in your learning.
- Bootcamps are usually inexpensive and less time-consuming in comparison to traditional degree courses.
- Most bootcamps offer career advice, guide you through the job application process, and help you build your professional network.
- Bootcamps often involve group activities to improve your teamwork and communication skills.
- You’ll receive a certification upon completion, which will impress prospective employers and validate your learning.
Your Next Step toward a Career in Data
Data science is an incredibly rewarding field. Positions in this industry not only bring immense job satisfaction, but offer well-paid salaries, excellent job prospects, and job security. You’ll get the opportunity to harness the power of data and make insightful discoveries to push your company forward.
Our data science bootcamp is a great place to start your journey. If you want to ease into the field and start with a little self-learning, you can also head over to our data science blog. You’ll find many more articles on the topic of big data including what it’s like to work as a data scientist.