Data science and machine learning are two of the hottest jobs in the IT sector. Businesses and companies are eagerly hiring data and ML professionals who can help them extract valuable information from data or develop a system that can make better decisions.
The prospective candidate often gets confused about which career option is best for them. Salary comparison can be the deciding factor if you want to enter any one of these fields or need clarification about which one to choose.
Salary comparisons and the future growth trend will briefly indicate which field is better.
A detailed comparison will help you determine which career pays the most or what the future job trends in the fields are.
Let’s find out which field pays more: data science or machine learning.
Machine Learning vs. Machine Learning : Salary Comparison and Growth Rate
Here’s a brief salary and growth comparison between ML and Data science:
JOB GROWTH RATE
36% ( According to BLS.GOV)
Between 6 LPA to 20 LPA
Between 4LPA to25LPA
CURRENT MARKET VALUE
USD 240 Billion
According to Glassdoor, the number of job postings for data scientists is around 13847 in 2022. MNCs like Amazon have thousands of vacant data scientist job postings.
Demand is relatively high; thus, according to the current seniority scale, pay is also at an all-time high. The average salary of a data scientist in India ranges from ₹4 LPA to ₹20 LPA, depending on your experience and skills. The basic pay structure of an Indian data scientist based on experience is:
Now, let’s find out how well ML engineers are paid.
Turns out that the pay scale is also quite high for ML as compared to other fields. The average salary of an ML engineer ranges from ₹3 LPA to ₹20 LPA, with the salary structure depending on your experience.
Below is a complete analysis of the salary structure of ML engineers in India.
What pays more, data science or machine learning?
From the above data, we can say ML engineers have a slightly higher pay scale than data scientists. The difference in pay depends on various factors. ML engineers are paid well because of their high demand, or maybe they need to master more technical skills.
To understand the slight difference in the pay scale of machine learning and data science, we have to focus on what they do.
So, let’s look at the job responsibilities of both data scientists and ML engineers.
Why are ML engineers paid more?
ML engineers’ primary responsibilities include developing a program or model to think and imitate human intelligence. In other words, ML engineers design, develop and implement ML systems that can make rational decisions based on past events.
On the other hand, data scientists gather, process, analyze, and visualize big data to extract meaningful insights. These insights are then used to make further business decisions. Extracting insights requires knowledge of statistics, programming, and mathematics, while ML engineers focus on algorithms and programming.
In general, ML engineers deal with more complex technical problems.
Through this analysis, we can conclude why ML engineers are often paid more. Although machine learning and data science are still in their early stages, there are some emerging jobs that you should be aware of.
What are the other related fields?
Data science and machine learning are vast fields. All the responsibility becomes a burden for a single person. Regardless of the reason, it appears that the field of data science is branching.
These are the top categories: Business Analytics and Intelligence, Business Analysis, Market Research Analysts, Data Engineering, and Data Management
For instance, the salary of a data engineer ranges from ₹4 LPA to ₹20 LPA per year, on the other hand, the average salary of a research analyst is around ₹2.1 LPA to ₹6.2 LPA.
All these fields are relatively low-paying, but these jobs can help you land high-paying jobs. . These job positions can add relevant experience to your portfolio. Whether you want to become a data scientist or an ML engineer, these jobs are the pathway that leads to a better high-paying job.
ML engineer salary
ML engineers’ salaries range from ₹4 LPA to ₹20 LPA. Well, that’s not true in all cases. A variety of factors influence payscale. Below, we have mentioned some of them.
- Company: According to the ambition box, an ML data engineer’s salary ranges between ₹4.2 lakhs and ₹28.5 lakhs, with an average of 13.9 lakhs. At the same time, TCS offers range from ₹ 3 lakh per month to ₹ 7.2 lakh per month.
- Experience: The annual salary of a machine learning engineer is approximately Rs 6.9 lakhs. A junior machine learning engineer earns around three lakhs per year, while mid-level and experienced machine learning engineers’ pay scales range from ₹3 lakhs per year to ₹20 lakhs per annum.
- Skill: Freshers in the field of ML earn around ₹3.9 lakhs with a core skill set in machine learning, data analysis, python, analytical skills, and computer science. In contrast, senior ML engineers earn an average of ₹16 LPA with a core skill set in artificial intelligence, python, deep learning, SQL, and machine learning.
Data scientist salary
Similar to ML engineers, a variety of factors influence the pay scale of data scientists. Let’s find out more about these factors::
- Company: TCS’s data scientist packages range from ₹5 LPA to ₹10 LPA, whereas Amazon’s packages range from ₹7.7LPA to 23LPA.
- Experience: A fresher data scientist earns around Rs. 4 lakhs per year on average, whereas a mid-level and experienced data scientist earns between Rs. 5 lakh and Rs. 25 lakhs per year.
With experience, both occupations touch the 20- to 25-lakh mark per year.
Which career pays more – data science or machine learning?
Although both these fields are at their peak, you will see exponential growth in these fields in the future. Whichever field you choose, it can pay more than the current trends. But when we compare data science with machine learning, machine learning engineers are slightly paid more than data scientists.
If you still need clarification, consider looking for other factors, such as core skills, roles & responsibilities.
If you are looking to kickstart your career in any one of these fields then what better place to begin than here at Skolar.