AI Engineer Vs Data Scientist, Salary, Job Description, Scope 2024

AI Engineer vs Data Scientist: The AI Engineer and Data Scientist are the two most important domains in 2024. Data scientist is a stable career with no limits. AI also joins the race as one of the most trending technologies that is taking on the world at a rapid pace. However, they share some major differences, which we will discuss in this article. Let us learn in detail about AI engineers vs data scientists.

AI Engineer Vs Data Scientist: An Overview

What are AI Engineers?

Artificial intelligence is one of the most famous and trending technologies in 2024. With the rapid expansion of AI in our day-to-day life, the need for skilled AI Engineers who are skilled in Artificial intelligence is in demand.

AI Engineers are responsible for designing and building the overall structure of an AI System. They are responsible for creating and managing a powerful algorithm to handle the complete AI-powered applications.

What are data scientists?

Data scientists are professionals who use different algorithms, maths, engineering and management skills to extract meaningful and powerful insights from a large collection of data. They use various tools like SQL, R, Python, Spark, Hadoop, etc. They are the most important elements of an organisation as they provide important information regarding market trends, risk analysis, business risks, potentials, etc.

AI Engineers Vs Data Scientists: Skills Required

There are some important skills and qualifications required to become data scientists and AI Engineers. Let us know the skills required for the two most trending job roles.

Skills Required for AI Engineers

Candidates must have a good hold over a programming language like Python, R, etc.
Must be fluent in math and statistics.
Candidates have a good knowledge of data structures and algorithms.
Must have a good knowledge of LINUX-based operating systems and commands.
Candidates must have a good command of machine learning and deep learning techniques.
Also, knowledge of algorithm development is required.

Skills Required for Data Scientists

Learning for a data scientist’s job role is a never ending responsibility. You need to have a good knowledge of the trending technologies of the world.

Candidates must have a strong knowledge of maths and statistics.
Good programming knowledge. Usually, data scientists prefer Python and R.
Candidates must have a good command of and knowledge of databases. SQL knowledge is also required.
Can solve queries related to relational databases.
Also, you must have a good knowledge of machine learning and data visualization techniques.

For both these job roles, you must have some analytical skills, such as critical thinking, problem-solving, experimentation, etc. Also, communication skills are required, such as domain knowledge, communication skills, collaboration, and time management is very important.

Also read: What is Data Science?

AI Engineer vs Data Scientist: Job Roles and Responsibilities

The job roles of data scientists and AI engineer is broad. They need to keep themselves updated with the latest advancements and AI-related technologies to find the application of cutting-edge technologies.

Job roles of a Data scientists

Data scientists are an important element of an organization who are responsible for extracting important information from a pool of data.
They must be able to analyze risks and provide business solutions.
They are responsible for preparing, cleaning, and transforming the raw datasets to extract information from them.
They need to work closely with the business partner and stakeholders to determine important issues related to the business.
They also must identify the future or present gas in the existing methods.
They can easily implement machine learning algorithms to prepare an appropriate solution to a traditional problem.
They can use various machine learning and statistical algorithms to improve the existing models.
Data scientists can implement various machine-learning algorithms to detect patterns, trends and correlations in a large dataset.
They also coordinate with the data analysts and data engineers to provide insights to various business stakeholders in a convincing way.

Job roles of AI Engineer

AI Engineers are responsible for creating AI algorithms and making them work.
They develop essential technologies to implement the models.
They need to maintain the structure and architecture of the AI Models.
They also have to deploy the models, test them and maintain them.
They must study and develop trending technologies using deep learning, machine learning and data analytics techniques.
They need to work directly with the customers to understand their needs and create a potential solution for the future.
They need to build and maintain the deep learning libraries using C++ and object-oriented design.
They can develop test environments for new hardware and platforms, including emulators and simulators for future hardware and chips.

Also read: What is Artificial Intelligence (AI)

AI Engineer vs Data Scientists: Qualification Required

Here are some of the important educational qualifications for AI engineers and Data scientists.

Required Qualifications for Data Scientists

A bachelor’s degree in Quantitative discipline (Economics, economics, computer science engineering, math, statistics, science).
An experience of one to two years in analytics and management techniques.
Must have a good knowledge of at least one programming language, like Python, R, or SAS.
Experience in at least one visualization tool such as Tableau, or Qilkview.
Candidates must have a good experience with project management.

Required Qualifications for AI Engineer

Candidates must have at least good experience (5-10 years) in Deep learning techniques and high-performance computing and system software development techniques.
A bachelor’s degree from a recgonized university in a related discipline.
Strong knowledge of C/C++, Python programming, Software system design, AI Algorithms, and data structures.
Knowledge of software engineering practices and principles.

AI Engineer vs Data Scientist: Salary

The salary level of data scientists and AI Engineers is sky-high. These job roles are always in demand, and recruiters are looking for candidates with good skills and experience levels to join the company. The pay scale differs based on the companies and places where candidates are offered the job role.

However, as AI is one of the most trending technologies, the average salary of an AI engineer is comparatively higher than that of a data scientist. However, data scientists are always in demand and are paid well.

Also read: Statistics for Data Science

Difference Between AI Engineer vs Data Scientist

Let us analyze the important difference between an AI Engineer and a Data scientist.

AI Engineer vs Data Scientist
AI Engineer	Data Scientist
AI Engineers are responsible for automating the system.	They study data and predict important patterns and trends.
They deploy and create AI Algorithms	They prepare, clean, transform, and explore data for analysis.
Develop APIs that are flexible and reliable.	They use various analytical methods and machine learning to identify and study patterns and correlations in a dataset.
Strong mathematics and statistics foundation.	Solid mathematics and algorithm knowledge.
Data visulaization is not a major requirement for the AI engineer.	Data visualization tools such as Tableau, Quilk View, and others
AI Engineers design the overall system of an AI Application	Data scientists analyze the data to extract important, meaningful insights, pattern and trends.
They are responsible for creating and optimizing the power of AI Applications.	Data Scientists identify and engineer relevant features from raw data to improve the performance of the model.
They need to maintain and optimize their AI Models.	They are not responsible for the maintenance of Applications.

Similarities Between AI Engineer vs Data Scientist

Both of these technologies study trending technologies to provide an effective solution for existing issues.
AI engineers and Data scientists require almost complete knowledge of important technical skills such as Python programming and maths, statistics, and analytical skills.
Both these job role requires knowledge of at least one of the following programming languages, Python or R.
They both have a good knowledge of machine learning tools and deep learning techniques.

AI Engineer vs Data Scientist FAQs

What are the roles of AI Engineers?

What is the job role of a data scientist?

Data scientists are professionals who use different algorithms, maths, engineering and management skills to extract meaningful and powerful insights from a large collection of data.

Who get paid higher, data scientists or AI engineer?

Can AI engineers become data scientists?

Yes, an AI Enigneer can easily become a data scientist as most of the skills and job descriptions for an AI Enigneer match data scientists. However, candidates need to master data analysis techniques and tools required for a data scientist.