The field of data science is a complex discipline filled with professionals that have extensive knowledge of analysis tools, techniques, and practices for dealing with big data. Those interested in becoming data scientists must possess various skills in programming, business, and software engineering.
If you want to pursue a career in data science, keep reading. In this article, you’ll learn how much data scientists make annually and learn more about what data scientists do. We’ll cover everything you need to know before making that first step toward your dream job.
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What Is Data Science?
Data science involves professionals being given large sets of data and making sense of the information. These professionals will use various techniques, analytics, and statistical or visualization tools to unpack the meaning of the information they have acquired. Typically, this data is used to build predictive models and aid in current and future business processes.
What Do Data Scientists Do?
A data scientist is in charge of taking large amounts of data and analyzing it in depth before delivering it to whoever has requested it. This data is designed to provide the company, team, or individual with actionable insights into what is being analyzed by identifying trends.
- Collect the data. The first stage of the data science process involves collecting the data and transforming it into numerical values. These values will later be manipulated by a computer to create a set of understandable data. The tasks in this phase include data entry, data acquisition, and data extraction.
- Maintain the data. This is where the data scientist “cleans” the data, categorizes it, processes it, and turns it into something useful. The tasks during this stage include data cleansing, data processing, and data staging.
- Process the data. After collecting and cleaning the data, the information acquired must be processed. This requires the scientist to comb through the data to find trends, ranges, and valuable information. This phase includes classifying and modeling the data.
- Analyze the data. During this stage, the data scientist will thoroughly examine the information and perform different analysis techniques. The tasks involved in this phase include qualitative and predictive analysis and text mining.
- Communicate the findings. In this final step, the data scientist must share their results and transform them into visual representations to be easily understood. At this stage graphs and charts can be used, and the reports produced will aid in making critical, informed decisions.
How Much Do Data Scientists Make?
Data scientists earn an annual salary of around $97,000. However, finding the appropriate work often means looking for a job with a salary that fits your needs and lifestyle. Careers in the tech industry, specifically in data science, are a great option, as the average wage is typically higher than in other industries.
Data Science Average Salaries
According to Payscale, the average data scientist’s annual salary is $97,004, or $36.62 an hour. However, this amount fluctuates based on experience level and job title. Typically, data scientists also get health benefits like medical, dental, and vision insurance, but that is dependent on the company you are working for.
What Is the Job Growth for Data Science?
The job outlook for data science careers is high. According to the US Bureau of Labor Statistics, computer and information research scientists’ jobs are expected to grow by 22 percent between 2020 and 2030, which is much faster than the average growth rate.
The Highest-Paying Types of Data Science Jobs in 2022
- Data Architect | $122,718
- Infrastructure Architect | $112,995
- Machine Learning Scientist | $112,343
- Data and Analytics Manager | $99,121
- Data Scientist | $97,004
- Data Engineer | $92,999
- Quantitative Analyst | $85,069
- Business Intelligence Developer | $81,924
- Data Storyteller | $62,541
- Operations Analyst | $58,832
Aside from knowing what compensation package you will receive, a basic understanding of the job description is vital for determining whether you are suited for a specific role. Finding a job that you can picture yourself doing, in the long run, requires conducting some research about the profession you want.
- Average Salary: $122,718
Data architects are skilled professionals who take a businesses’ needs and transform them into data that can be managed. Data architects use their expertise in computer design to create database systems. These systems will allow the business to collect big data that will be organized and structured through the data science process.
- Average Salary: $112,995
Infrastructure architects design and deploy information systems that help support a company’s infrastructure. They also address any ICT security and performance-related issues while managing the software and hardware installations. They evaluate system requirements, provide alternative solutions, observe new systems, and integrate them.
Machine Learning Scientist
- Average Salary: $112,343
Machine learning scientists are data scientists who create machine learning models and work with big data. Their machine learning techniques help them clean and interpret the data and build a machine learning algorithm based on the model they created from analyzing the data.
Data and Analytics Manager
- Average Salary: $99,121
These managers direct teams of analysts and oversee the work happening in the analytics sector of a company. They are responsible for ensuring their team is accurate in their analytic procedures while developing new processes for data analysis. Professionals in this role should have analytics and business skills.
- Average Salary: $97,004
Data scientists obtain big sets of data and analyze and process them through the five different stages of analysis mentioned previously. Their technology and social science skills help locate trends within the data and compile them into a neat set that will provide essential business insight.
- Average Salary: $92,999
Data engineers design systems that help collect, store, and analyze data. Without data engineers to process the data, machine learning and deep learning specialists would be unsuccessful in their jobs.
- Average Salary: $85,069
Quantitative analysts are the professionals responsible for helping companies make financial decisions. This is done through quantitative methods of handling bit data and by creating algorithms that help process data. Their role is essential as they help companies with investment decisions and risk management.
Business Intelligence Developer
- Average Salary: $81,924
Business intelligence developers are responsible for creating and implementing business intelligence interfaces, like query tools, interactive dashboards, and data modeling tools. However, the business intelligence sector can be divided into distinct layers, such as the data source, the warehouse, and the reporting layers, all of which are responsible for different tasks.
- Average Salary: $62,541
Data storytellers tell the narrative of sets of data, with visual aids to make it understandable, compelling, and appealing. These professionals explain what is happening within the data and provide a visual representation to ensure that the audience will understand the information presented to them.
- Average Salary: $58,832
Operations analysts review a company’s infrastructure, like their policies and procedures, and advises on potential improvements. These professionals obtain internal data from within the company and formulate a feedback report that will help enhance the company’s performance.
Data Science Career Path
Like other career paths in the tech industry, there is no single way to progress through this industry. However, there are certain steps most data scientists take to succeed and progress.
- Obtain the necessary skills and training. Before landing a job as a data scientist, you’ll need training to hone the skills needed to succeed. This can be done through an undergraduate degree or a data science bootcamp. Obtaining programming skills will help you become a better data scientist.
- Secure an entry-level job. Once you’ve gained the specialized skills you need to accomplish your career goals, it is time to look for an entry-level position. You should focus on one niche that interests you, like artificial intelligence or operation analysis, and move toward that. You can find an internship in that niche and create a portfolio to showcase your skills and projects.
- Move up the company ladder. After acquiring an entry-level job, you can focus on moving up the career ladder. However, if you don’t see yourself being offered a promotion, move to a different company that could use your abilities. Over time, you will progress from a mid-level to a senior-level position. Ensure you have the proper qualifications for the job, such as a Bachelor’s Degree in Data Analytics.
- Move into a director’s role. After demonstrating your competence in mid-level and senior-level positions, you may be promoted to the position of director. Directors are highly skilled professionals that oversee junior data scientists. Typically they will have a master’s degree or PhD in a relevant field, but it is possible to be promoted without these qualifications.
- Go beyond data science. It may seem far into the future from where you are in your data science career path, but there is room to grow beyond just data science. With many companies requiring a data science team, you might find yourself on a career trajectory you never thought possible. Different sectors where you can apply your data science skills include healthcare, travel agencies, and finance.
Should You Become a Data Scientist?
You should become a data scientist if you enjoy a challenge, a good annual salary, and the potential to work remotely. All these factors should make data scientists happy with their career choice. Although everyone can become a data scientist, not everyone can make a long-term career out of it.
Data science can be difficult. It requires hard work from individuals with exceptional problem-solving, mathematical, analytical, and technological skills. The abilities acquired by these professionals are often the result of years of experience. However, if you can put in the hard work, are willing to learn, and can commit time to pursue this field, a career in data science might be for you.
Types of Data Science Careers FAQ
Yes, data scientists are in high demand. According to the US Bureau of Labor Statistics, computer and information research scientists have a job outlook of 22 percent, which is substantially faster than average.
AI engineers and data scientists collaborate yet hold different basic responsibilities. Each professional is essential and in great demand as the job market for data science careers continues to grow and thrive.
Yes, data science is hard to study. With data science being such a broad topic, it can be difficult and intimidating for an individual just entering into the field. However, it will become easier over time with the proper guidance and teaching.
The number of years it takes to become a data scientist depends on the path you take. Someone taking the university route could become a data scientist within three or four years. Those wanting to obtain further education will accomplish their goals of becoming data scientists in five or six years. However, it is possible to take online beginner classes in data science to get a head-start on the process. Data science bootcamps would be an excellent option for this.
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