Top Job Roles With Their Salary Data in the World of Data Science for 2020–2022

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13rd Jun, 2022
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12nd Sep, 2020
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Top Job Roles With Their Salary Data in the World of Data Science for 2020–2022

Data Science requires the expertise of professionals who possess the skill of collecting, structuring, storing, handling and analyzing data, allowing individuals and organizations to make decisions based on insights generated from the data. Data science is woven into the fabric of our daily lives in myriad ways that we may not even be aware of; starting from the online purchases we makeour social media feeds, the music we listen to or even the movie recommendations that we are shown online 

For several years in a row, the job of a data scientist has been hailed as the “hottest job of the 21st century”. Data scientists are among the highest paid resources in the IT industry. This is why it is important to be a certified professional and one can be the same by taking a data science course. According to Glassdoor, the average data scientist’s salary is $113,436. With the growth of data, the demand for data science job roles in companies has been rising at an accelerated pace. 

Know more about measures of dispersion.

How Data Science is a powerful career choice 

The landscape of a data science job is promising and full of opportunities spanning different industries. The nature of the job allows an individual to take on flexible remote jobs and also to be self-employed 

The field of data science has grown exponentially in a very short time, as companies have come to realize the importance of gathering huge volumes of data from websites, devices, social media platforms and other sources, and using them for business benefits. Once the data is made available, data scientists use their analytical skills, evaluate data and extract valuable information that allows organizations to enhance their innovations. 

A data scientist is responsible for collecting, cleansing, modifying and analyzing data into meaningful insights. In the first phase of their career, a data scientist generally works as a statistician or data analyst. Over many years of experience, they evolve to be data scientists.  

The ambit of data has been increasing rapidly which has urged companies to actively recruit data scientists to harness and leverage insights from the huge quantities of valuable data available, enabling efficiency in processes and operations and driving sales and growth 

In the future, data may also emerge as the turning point of the world economy. So, pursuing a career in data science would be very useful for a computer enthusiast, not only because it pays well but also since it is the new trend in IT. 

According to the Bureau of Labor Statistics (BLS), jobs for computer and information research scientists, as well as data scientists are expected to grow by 15 percent by the year 2028. 

Who is a Data Scientist & What Do They Do? 

Data Scientists are people with integral analytical data expertise together with complex problem-solving skills, besides the curiosity to explore a wide range of emerging issues. To be an expert in the field, you must take the data science bootcamp training

They are considered to be the best of both the sectors – IT and business, which makes them extremely skilled individuals whose job roles straddle the worlds of computer sciencestatistics, and trend analysis. Because of this surging demand for data identification and analysis in various tech fields like AI, Machine Learning, and Data Science, the salary of a data scientist is one of the highest in the world. 

Requisite skills for a data scientist 

Before we see the different types of jobs in the data analytics field, we must be aware of the prerequisite skills that make up the foundation of a data scientist: 

  • Understanding of data – As the name suggests, Data Science is all about data. You need to understand the language of data and the most important question you must ask yourself is whether you love working with data and crunching numbers. And if your answer is “yes”, then you’re on the right track. 
  • Understanding of algorithms or logic – Algorithms are a set of instructions that are given to a computer to perform a particular task. All Machine Learning models are based on algorithms, so it is quite an essential prerequisite for a would-be data scientist to understand the logic behind it.  
  • Understanding of programming  To be an expert in data science, you do not need to be an expert coder. However, you should have the foundational programming knowledge which includes variables, constants, data types, conditional statements, IO functions, client/server, Database, API, hosting, etc. If you feel comfortable working with these and you have your coding skills sorted, then you’re good to go. 
  • Understanding of Statistics  Statistics is one of the most significant areas in the field of Data Science. You should be well aware of terminologies such as mean, median, mode, standard deviation, distribution, probability, Bayes’ theorem, and different Statistical tests like hypothesis testing, chi-square, ANOVA, etc. 
  • Understanding of Business domain – If you do not have an in-depth working knowledge of the business domain, it will not really prove to be an obstacle in your journey of being a data scientist. However, if you have the primitive understanding of the specific business area you are working for, it will be an added advantage that can take you ahead. 

Apart from all the above factors, you need to have good communication skills which will help the entire team to get on the same page and work well together.

Data Science Job Roles  

Data science experts are in demand in almost every job sector, and are not confined to the IT industry alone.  

Let us look at some major job roles, associated responsibilities , and the salary range: 

1. Data Scientists

A Data Scientist’s job is as exciting as it is rewarding. With the help of Machine Learning, they handle raw data and analyze it with various algorithms such as regression, clustering, classification, and so on. They are able to arrive at insights that are essential for predicting and addressing complex business problems.  

Responsibilities of Data Scientists 

The responsibilities of Data Scientists are outlined below: 

  • Collecting huge amounts of organized and unorganized data and converting them into useful insights. 
  • Using analytical skills like text analytics, machine learning, and deep learning to identify potential solutions which will help in the growth of organizations. 
  • Following a data-driven approach to solve complex problems.  
  • Enhancing data accuracy and efficiency by cleansing and validating data. 
  • Using data visualization to communicate significant observations to the organization’s stakeholders. 

Data Scientists Salary Range 

According to Glassdoor, the average Data Scientist salary is $113,436 per annum. The median salary of an entry-level professional can be around $95,000 per annum. However, early level data scientists with 1 to 4 years' experience can get around $128,750 per annum while the median salary for those with more experience ranging around 5 to 9 years  can rise to an average of $165,000 per annum. 

2. Data Engineers  

A Data Engineer is the one who is responsible for building a specific software infrastructure for data scientists to work. They need to have in-depth knowledge of technologies like Hadoop and Big Data such as MapReduce, Hive, and SQL. Half of the work of Data Engineers is Data Wrangling and it is advantageous if they have software engineering background. 

Responsibilities of Data Engineers  

The responsibilities of Data Engineers are described below: 

  • Collecting data from different sources and then consolidating and cleansing it. 
  • Developing essential software for extracting, transforming, and loading data using SQL, AWS, and Big Data. 
  • Building data pipelines using machine learning algorithms and statistical techniques. 
  • Developing innovative ways to enhance data efficiency and quality. 
  • Developing, testing and maintaining data architecture. 

Required Skills for Data Engineers  

There are certain skill sets that data engineers need to have: 

  • Strong skills in analytics to manage and work with massive unorganized datasets. 
  • Powerful programming skills in trending languages like Python, Java, C++, Ruby, etc. 
  • Strong knowledge of database software like SQL and experience in relational databases. 
  • Managerial and organizational skills along with fluency in various databases.  

Data Engineers Salary Range 

According to Glassdoor, the average salary of a Data Engineer is $102,864 in the USA. Reputed companies like Amazon, Airbnb, Spotify, Netflix, IBM value and pay high salaries to data engineers. Entry-level data and mid-range data engineers get an average salary between $110,000 and $137,770 per annum. However, with experience, a data engineer can get up to $155,000 in a year. 

3. Data Analyst 

As the name suggests, the job of a Data Analyst is to analyze data. A data analyst collects, processes, and executes statistical data analyses which help business users to develop meaningful insights. This process requires creating systems using programming languages like Python, R or SAS. Companies ranging from IT, healthcare, automobile, finance, insurance employ Data Analysts to run their businesses efficiently.  

Responsibilities of Data Analysts  

The responsibilities of Data Analysts are described below: 

  • Identifying correlations and gathering valuable patterns through data mining and analyzing data. 
  • Working with customer-centric algorithms and modifying them to suit individual customer demands. 
  • Solving certain business problems by mapping data from numerous sources and tracing them. 
  • Creating customized models for customer-centric market strategies, customer tastes, and preferences. 
  • Conducting consumer data research and analytics by deploying statistical analysis. 

Data Analyst Salary Range 

According to Glassdoor, the national average salary of a Data Analyst is $62,453 in the United States. The salaries of an entry-level data analyst start at  

$34,5000 per year or $2875 per month.  Glassdoor states that a junior data analyst earns around $70,000 per year and experienced senior data analysts can expect to be paid around $107,000 per year which is roughly $8916 per month. 

Key Reasons to Become a Data Scientist 

Becoming a Data Scientist is a dream for many data enthusiasts. There are some basic reasons for this: 

1. Highly in-demand field 

The job of Data Science is hailed as one of the most sought after jobs for 2020 and according to an estimate, it is predicted that this field would generate around 11.5 million jobs by the year 2026. The demand for expertise in data science is increasing while the supply is too low.  This shortage of qualified data scientists has escalated their demand in the market. A survey by the MIT Sloan Management Review indicates that 43 percent of companies report that a major challenge to their growth has been a lack of data analytic skills. 

2. Highly Paid & Diverse Roles 

Since data analytics form the central part of decision-making, companies are willing to hire larger numbers of data scientists who can help them to make the right decisions that will boost business growth. Since it is a less saturated area with a mid-level supply of talents, various opportunities have emerged that require diverse skill sets. According to Glassdoor, in the year 2016,  data science was the highest-paid field across industries. 

3. Evolving workplace environments 

With the arrival of technologies like Artificial Intelligence and Robotics which fall under the umbrella of data science, a vast majority of manual tasks have been replaced with automation.  Machine Learning has made it possible to train machines to perform repetitive tasks , freeing up humans to focus on critical problems that need their attention. Many new and exciting technologies have emerged within this field such as Blockchain, Edge Computing, Serverless Computing, and others.  

4. Improving product standards 

The rigorous use of Machine Learning algorithms for regression, classification recommendation problems like decision trees, random forest, neural networks, naive Bayes etc has boosted the customer experiences that companies desire to have. One of the best examples of such development is the E-commerce sites that use intelligent Recommendation Systems to refer products and provide customer-centric insights depending upon their past purchases. Data Scientists serve as a trusted adviser to such companies by identifying the preferred target audience and handling marketing strategies. 

5. Helping the world 

In today’s world, almost everything revolves around data. Data Scientists extract hidden information from massive lumps of data which helps in decision making across industries ranging from finance and healthcare to manufacturing, pharma, and engineering. Organizations are equipped with data-driven insights that boost productivity and enhance growth, even as they optimize resources and mitigate potential risks. Data Science catalyzes innovation and research, bringing positive changes across the world we live in. 

Factors Affecting Data Scientist’s Salary 

The salaries of Data Scientists can depend upon several factors. Let us study them one by one and understand their significance: 

Data Scientist Salary by Location 

The number of job opportunities and the national data scientist salary for data innovators is the highest in Switzerland in the year 2020, followed by the Netherlands and the United Kingdom. However, since Silicon Valley in the United States is the hub of new technological innovations, it is considered to generate the most jobs for startups in the world, followed by Bangalore in India. A data scientist’s salary in Silicon Valley or Bangalore is likely to be higher than in other countries. Below are the highest paying countries for data scientist roles along with their average annual data science salary: 

Switzerland$115,475
Netherlands$68,880
Germany$64,024
United Kingdom$59,781
Spain$30,050
Italy$37,785

Data Scientist Salary by Experience

A career in the field of data science is very appealing to young IT professionals. Starting salaries are very lucrative, and there is incremental growth in salary  with  experience. Salaries of a data scientist depend on the expertise, as well as the years of experience: 

  • Entry-level data scientist salary – The median entry-level salary for a data scientist is around $95,000 per year which is quite high. 
  • Mid-level data scientist salary    The median salary for a mid-level data scientist having experience of around 1 - 4 years is $128,750 per year. If the data scientist is in a managerial position, the average salary rises upto $185,000 per year. 
  • Experienced data scientist salary   The median salary for an experienced data scientist having experience of around 5 - 9 years is $128,750 per year whereas the median salary of an experienced manager is much higher; around $250,000 per year. 

Data Scientist Salary by Skills 

There are some core competencies that will help you to shine in your career as a Data Scientist, and if you want to get the edge over your peers you should consider polishing up these skills: 

  • Python is the most crucial and coveted skill which data scientists must be familiar with, followed by R. The average salary in the US for  Python programmers is $120,365 per annum. 
  • If you are well versed in both Data Science and Big Data, instead of just one among them, your salary is likely to increase by at least 25 percent . 
  • The users of innovative technology like the Statistical Analytical System get a salary of around $77,842. On the other hand, users of software analysis software like SPSS have a pay scale of  $61,452 per year. 
  • Machine Learning Engineers on the average earn around $111,855 per year. However, with more experience in Machine Learning along with knowledge in Python, you can earn around $146,085 per annum. A Data Scientist with domain knowledge of Artificial Intelligence can earn an annual salary between $100,000 to $150,000. 

Extra skills in programming and innovative technologies have always been a value-add that can enhance your employability. Pick skills that are in-demand to see your career graph soar. 

Data Scientist Salary by Companies 

Some of the highest paying companies in the field of Data Science are tech giants like Facebook, Amazon, Apple, and service companies like McGuireWoods, Netflix or Airbnb.  

Below is a list of top companies with the highest paying salaries: 

McGuireWoods$165,114
Amazon$164,114
Airbnb$154,879
Netflix$147,617 
Apple$144,490
Twitter$144,341
Walmart$144,198
Facebook$143,189
eBay$143,005

Salaries of Other Related Roles 

Various other job roles associated with Data Science are also equally exciting and rewarding. Let us look at some of them and their salaries: 

Machine Learning Engineer$114,826
Machine Learning Scientist$114,121
Applications Architect$113,757
Enterprise Architect$110,663
Data Architect$108,278
Infrastructure Architect$107,309
Business Intelligence Developer$81,514
Statistician$76,884

Conclusion

Let us look at what we have learned in this article so far: 

  • What is Data Science? 
  • The job of a Data Scientist 
  • Pre-requisite skills for a Data Scientist 
  • Different job roles 
  • Key reasons for becoming a Data Scientist 
  • Salary depending upon different factors 
  • Salary of other related roles 

The field of Data Science is ripe in terms of opportunities for Data Scientists, Data Engineers, and Data Analysts. Meanwhile, opt for knowledgehut data science course to be a certified professional. 

The figures mentioned in this article are not set in stone and may vary depending upon the skills you possess, experience you have and various other factors. With more experience and skills, your salary is bound to increase by a certain percentage every year. Data science is a field that will revolutionize the world in the coming years and you can have a share of this very lucrative pie with the right education qualifications, skills, experience and training.  

Profile

Priyankur Sarkar

Data Science Enthusiast

Priyankur Sarkar loves to play with data and get insightful results out of it, then turn those data insights and results in business growth. He is an electronics engineer with a versatile experience as an individual contributor and leading teams, and has actively worked towards building Machine Learning capabilities for organizations.