Machine Learning/AI Engineer Vs Data Scientist: The Career Path You Should Choose
Right now, Machine Learning/Artificial Intelligence and Data Science are two of the most desired career paths. The sixth edition of DOMO’s report states that around 2.5 Quintillion bytes of data are generated every day. A professional, who can manage vast data day-to-day for business’s betterment, is not less than a superhero. The line between Machine Learning/ Artificial Intelligence and Data Science is diminishing with an increase in the competition between them.
Let us begin with the comparison between both the career paths to conclude which one is better.
Data Science: Data Scientist
Among all the definitions available for data scientists, the easiest to understand is ‘data scientists are the professionals who practice data science’. With their expertise in data science algorithms, data scientists solve complex data-related problems for businesses. Data scientists possess image and video processing, speech, medicine and material simulation, text analytics (NLP), etc.
Machine Learning/ Artificial Intelligence: Machine Learning/ Artificial Intelligence Engineer
Machine learning engineers are programmers who develop machines and systems that can learn to process independently without any further assistance or instructions. The focus of these computer programmers goes explicitly ahead of programming machines to perform particular tasks. ML/ AI engineers programmes machines so that they are enabled to take actions without any instructions or directions further.
MACHINE LEARNING/AI ENGINEER VS DATA SCIENTIST:
During 2012, a lot of job opportunities for data scientists flooded the market. Although the machine learning engineer role is relatively new, the same is happening for the job role. ML/ AI job roles are bussing in the places where data scientists have already emerged.
Let us have a look at the Salary Insights for both the job roles:
Average Salary of a Data Scientist:
According to PayScale, a Data Scientist’s average salary in India is INR 708,012; it is $96,106 in the United States of America. The salary depends on the company, location, job profile, work profile, and other factors.
| Experience | Salary |
| Entry Level (India) | INR 306,054 – INR 1,215,966 |
| Entry Level (US) | $ 306,054 – $ 1,215,966 |
| Entry Level (India) | INR 306,054 – INR 1,215,966 |
| Entry Level (US) | $ 306,054 – $1,215,966 |
Average Salary of a Machine Learning/ Artificial Intelligence Engineer:
The average salary of a Machine Learning Engineer in the United States of America is around $111,490; it is INR 719,646 in India. Comparing the job profiles’ salary trends, it can be seen that ML/ AI engineers earn a little more than a data scientist.
| Compensation | Salary |
| Salary | $76,953 – $151,779 |
| Bonus | $2,974 – $25,541 |
| Profit Sharing | $1,934 – $51,285 |
| Total Pay | $76,184 – $162,727 |
Job Trends:
Job trends of a Data Scientist:
28% rise in demand for data scientists has been seen in s2020. More and more industries are becoming data-driven, and they need skilled data scientists to hold the humongous data altogether for their business. According to the US Bureau of Labor Statistics, around 11.5 million jobs will be created by 2026.
job trends of a Machine Learning/ Artificial Intelligence Engineer:
By next year, an IDC report states that three-quarters of commercial enterprise applications could lean on artificial intelligence. By 2023, an Analytics Insight report says that there will be more than 20 million available artificial intelligence jobs.
Director of Veritone, an AI tech company, based in Costa Mesa, California, Gus Walker said that in 2021, there would be growing opportunities for artificial intelligence and machine learning specialities in different sectors public safety, banking, and fintech, and healthcare.
Skills Required:
Now let us look at the skills required to be a data scientist and machine learning engineer. Below we have given a standard skillset required for both the job roles.
Programming Languages:
The primary requirement of being a machine learning engineer and a data scientist is to be well acquainted with programming languages, preferably python. Python is one of the easiest languages to learn among all programming languages.
Although python alone cannot be helpful, you may also require knowledge of other languages like C++, R, Python, and Java. Also, at some point in your career, you might work on MapReduce.
Statistics:
Statistics is defined as the study of the collection, analysis, interpretation, presentation, and data organisation. Data scientists, as well as ML/ AI engineers, must be well familiar with statistics. Also, individuals must be well acquainted with Matrices, Vectors, and Matrix Multiplication.
Data Cleaning and Visualisation:
Data cleansing can help companies to save time and increase efficiency. Being able to tell a compelling story through data is essential to keep the audience engaged.
Data insights must be comfortable and understood. Or else it can become a bit difficult for you to communicate it to the audience. That is why data visualisation has a significant impact on the data.
Machine Learning and Neural Network Architectures:
Machine learning and predictive modelling are becoming trending topics nowadays. You must be familiar with different machine learning tools as well, like machine learning, decision trees, logistic regression, etc. These skills can help you to solve different prediction based analytical data problems.
SRM and LEARNXT are new-age path-breakers!
Considering the current fierce job market, SRM, in collaboration with LEARNXT, offers various machine learning/ artificial intelligence and data science courses. You will learn through case studies, presentations, assignments, and assessments. Also, the digital learning platform will provide you with hands-on experience with real-life projects.
Sridhar Nagarajachar (CEO, LEARNXT, SRM Group) commented “SRM Group and LEARNXT believe that we can empower people to achieve their dreams through education.Our learning focuses on knowing, doing and being aspects of skills and careers”.
Stay tuned to LEARNXT to know more about the best career path as a machine learning/ AI engineer or data scientist.
To know more, please click on, https://learnxt.com/home.php
