Why You Don't Need a Degree to Get Hired in Data Science

For the third year in a row, Data Scientist has been ranked the #1 career by Glassdoor. With a base salary averaging $117,345 per year and 11.5 million job openings expected by 2026, training for this role could be a great move for your career.

A data scientist cleans, manipulates, and organizes data. Skills include: distributed computing, predictive modeling, story-telling and visualizing, math, statistics, and machine learning. Popular languages include Python, R, SAS, MatLab, SQL, Hive, Pig, and Spark. Popular terms relating to data science include: big data, natural language processing, artificial intelligence and deep learning, among others.

While many data scientists have extensive training, such as a graduate degree in Computer Science or a related field, there alternatives to get started in the industry. For instance, data science coding bootcamps are becoming popular. Some more general fullstack software development bootcamps, particularly those focused on the Python programming language, also offer training in the skills you need. Programs are usually 12-26 weeks in length, depending on whether they are full or part time.

Typical Bootcamp Experience

In many bootcamps, students follow a predetermined curriculum that isn't especially personalized. Bootcamps, like recruiting agencies, aim to help students get started in a few specific types of jobs - software developer, in particular. Software development is only one of the many high-paying hats a bootcamp graduate is qualified to wear, though most bootcamp graduates learn little about the others. Bootcamp graduates have often gained the skills to be product managers, instructors, or many other types of technical positions and data related roles such as those listed below. Many of these can be stepping stones to a full-fledged data science position.

Roles In Data Science

1.) Data Analyst

Data Analysts collect and process data, and perform statistical data analysis. Analysts are proficient in R, Python, HTML, JavaScript, C/C++, and/or SQL. They typically need to be good with spreadsheet tools (e.g. Excel), database systems (SQL and NO SQL), communications and visualization, math, statistics, and machine learning. According to Glassdoor, the average salary for a Data Analyst is $67,377.

2.) Data Engineer

Data Engineers specialize in developing, constructing, testing, and maintaining systems. This role is similar to software engineering, in that the focus is on building and designing software. Languages used include SQL, Hive, Pig R, MatLab, SAS, SPSS, Python, Java, Ruby, C++, and Perl. Like Data Analysts, Data Engineers should have an understanding of database systems, data modeling and ETL tools, data APIs, and data warehousing solutions. According to Glassdoor, the average salary for a Data Engineer is $116,591.

3.) Business Analyst

A Business Analyst improves business processes and is an intermediary between business and IT. Typically, Business Analysts speak extensively with stakeholders to understand the problems to work on. According to Glassdoor, the average salary for a Business Analyst is $69,163.

4.) Statistician

Statistician is a less software infrastructure-heavy role than some of the others. Statisticians focus on designing and performing statistical analyses of data. They may perform these analyses in Python or R and interpret the results. They often create charts and other displays of the data and present their analyses. According to Glassdoor, the average salary for a Statistician is $82,477.

5.) Data Scientist

Data Scientists work on a variety of aspects of data analysis. They may design and build machine learning models, extend data using third-party sources of information, improve data collection, format data properly for analysis, and refine the data analysis pipeline. In addition to familiarity with statistics and modeling, this role also requires a software background. The average salary for a Data Scientist is $95,000-$165,000.

Getting There...

As mentioned, a coding bootcamp can be a viable option to accelerate your path to a data science career. In particular, a bootcamp that is data science specific and/or emphasizes Python ( a popular coding language in the data sciences) will give you the tools you'll need to both get started in the industry and build a successful, long-term career.

About Byte Academy

Byte Academy, headquartered in New York City, was the first coding bootcamp in the area to offer a full-time Python Fullstack Development program. Today, it also offers a specialized Data Science bootcamp in addition to industry-focused technical tracks such as FinTech (financial technology). It is the first bootcampt worldwide to offer such a program. In addition to New York, other campus locations include Houston, Texas and Bangalore, India. Its curriculum is also offered worldwide via a remote program.

Even before Byte Academy officially launched its data science course, many students entered data science-related fields after completing the school's Python Fullstack Development bootcamp. Python, the core language of Byte Academy's curriculum, is very efficient at analyzing layers of complex data and therefore is heavily used in quantitative fields such as finance and data science. The language is a favorite at leading tech companies too, such as Google, Instagram, YouTube and more. It is based on simplicity so it is great for beginners, and has been ranked as the most popular introductory coding language at US colleges. R, which is also popular in the data sciences, is much more difficult to learn, particularly for beginners.

Python has an extensive number of open-source libraries which are among the top in solving data-science related tasks and challenges. These include NumPy, Pandas, TensorFlow and more. If you are hesitant to commit fully to data science-specific education, a Python coding bootcamp like Byte Academy, may be a strong option to consider.

Student Success

Even though many started as pure beginners, the majority of graduates from Byte Academy's 14-week full-time or 24-week part-time program have entered data-science related roles. A quick search of the school on LinkedIn reveals that graduates hold a variety of job titles including Data Engineer, Data Analyst, Business Analyst, Machine Learning & Software Engineer, Deep Learning Engineer, and Data Scientist.

With an instructor-to-student ratio averaging less than 1:5, Byte Academy works closely with students to personalize learning tracks and career paths early on in their education. All students have a dedicated careers coach during and after the program. Byte Academy is a member of the Council For Integrity Results Reporting Standards ("CIRR"), and their CIRR report reveals that 90% of graduates are placed in a technology job within six months of graduation. Companies that students have gone on to work for include JP Morgan, Google, Apple, Goldman Sachs, Microsoft, Facebook and IBM.

In addition to 14 week full-time and 24 week part-time bootcamps, the school offers introductory workshops on Python and abbreviated summer bootcamps in 8 and 12 week formats.

Conclusion

All companies need skilled personnel to help make informed data-based decisions. As such, data science roles may be found in companies, non-profits, government organizations and more across industries and sizes. In fact, The Bureau of Labor Statistics expects that the need for skilled data science professionals will continue to rise, and that the job market will face a shortage of data science professionals. This means that more and more companies will hire for data science-based roles without requiring candidates to have higher degrees. Rather, programs such as coding bootcamps, real-world training, and more will be considered just as effective.

Want to learn more about Byte Academy?

Check out their website
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Email info@byteacademy.co

This post was sponsored by Byte Academy