AI Engineer v Data Scientist: Key Differences

Last updated by Nitin Grover on Sep 30, 2024 at 06:04 PM | Reading time: 7 minutes

Data Scientists and AI Engineers (Artificial Intelligence Engineers) are two distinct roles with overlapping skills. In small-sized organizations, the same employee fulfills the duties of both the data scientist and AI engineer. However, in larger organizations where roles are defined more clearly, there are separate positions for each role.

Data scientists utilize mathematical and statistical concepts, advanced analytical techniques, and machine learning algorithms to build models and extract valuable insights for informed decision making. On the other hand, Artificial Intelligence (AI) Engineers utilize their technical acumen to impart intellect to machines.

In this article, we identify the key differences between the job roles of a Data Scientist vs AI Engineer.

Also read: Top 9 Data Science Jobs Roles for Career Advancement in 2024

Data Scientist vs AI Engineer: What a Data Scientist Does?

As we compare the responsibilities of a data scientist vs AI engineer let’s first look at main responsibilities of a data scientist:

Gathering of data from various sources and ensuring that data collection and storage mechanisms are at place.
Cleaning and preprocessing of raw data to ensure that it’s accurate, complete, and consistent in every aspect
Use statistical techniques to identify patterns and trends in preprocessed data
Development, implementation and fine-tuning of machine learning models
Use insights drawn from data patterns to derive actionable recommendations for business strategy and operations
Use tools like Tableau and Power BI to create visualizations for presentation to stakeholders
Work with cross-functional teams to integrate data science solutions into business processes and products

Data Scientist vs AI Engineer: What an AI Engineer Does?

Now let’s look at the responsibilities of an AI Engineer:

Identify the overall stability of the AI system and identify areas of improvement
Create and deploy AI algorithms that are scalable, flexible and reliable
Develop and maintain architecture using leading AI frameworks
Implement continuous integration and versioning control in AI models to track model iterations and code updates.
Create user interfaces to deploy a more in-depth view of the models.
Implement concepts that aid in continuous delivery, auto-scaling, and application monitoring.
Develop MVP applications that encapsulate everything from model development to model testing.

Also read: How to Become an Artificial Intelligence Engineer?‍

Data Scientist vs AI Engineer: Average Salary Packages:

Here we provide the average salary packages that data scientists and AI engineers draw on per annum basis during various phases of their career. ‍

Data Scientist vs AI Engineer: Data Scientist Salaries

Entry-Level Data Scientist Salary (1-2 years): $84,386 per annum (June 2024, Glassdoor.com)
Data Scientist Salary (3-5 years): $1,56,641 per annum (June 2024, Glassdoor.com)
Senior Data Scientist Salary (5-8 years): $2,36,481 per annum (June 2024, Glassdoor.com)
Lead Data Scientist Salary (8-11 years): $2,48,811 per annum (June 2024, Glassdoor.com)

Data Scientist vs AI Engineer: AI Engineer Salaries

Entry-Level AI Engineer Salary (1-2 years): $115,158 per annum (June 2024, Talent.com)
Data Scientist AI Engineer Salary (3-5 years): $1,64,391 per annum (June 2024, Glassdoor.com)
Senior AI Engineer Salary (5-8 years): $2,31,899 per annum (June 2024, Glassdoor.com)
Lead AI Engineer Salary (8-11 years): $2,32,556 per annum (June 2024, Glassdoor.com)

Also, get a comprehensive insight into AI Engineer Salary in the USA.

Note: Salary data is accurate at the time of publishing this blog post and may change at source without prior information.

Data Scientist vs AI Engineer: Key Skill Differences

There are quite a few common skill sets between data scientists and AI engineers. For instance, both job roles need to have at least a graduate degree in computer science or a related field. In addition, both data scientists and AI engineers need to be proficient in at least one programming language like Python and mathematical and statistical concepts.

Now let’s identify some of the key skill sets that act as difference makers between data scientists vs AI engineers.

Let’s first look at the skills of a data scientist.

Along with having a degree in data science, computer science or computer engineering, a data scientist needs to be proficient with:

Mathematical and statistical concepts like calculus, regression analysis and probability
Knowledge of at least one programming language between Python or R programming languages
Knowledge of big data tools like Hadoop, Spark, Pig, Hive, and others
Proficiency in using SQL and querying in other relational database management systems
Proficiency in data visualization tools like Tableau, Power BI, etc.
Good understanding of data mining, data cleaning, and data management techniques

Now let’s identify the skills that an AI engineer has. Just like data scientists, AI engineers should also have fundamental knowledge of at least one programming language like Python, R, C++ or Java. ‍

Now let’s look at some key skill sets of AI engineers:

Expertise in SQL and NoSQL databases
Knowledge of big data tools like Apache Hadoop, Apache Spark, and Apache Cassedra as well as development tools like Bootstrap and Jira
Knowledge of machine learning algorithms and models
Strong understanding of data security and privacy measures
Strong interpersonal, communication, and problem-solving skills

Now let’s take a quick glance at some key differences between a data scientist vs AI engineer

Aspect	Data Scientist	AI Engineer
Primary Focus	Analyze and interpret complex data	Design, develop, and deploy AI/ML models
Languages Known	Proficiency in Python or R as well as SQL	Proficiency in Python, R, Java or C++ programming language as well as SQL and NoSQL databases
Tools & Frameworks	Pandas, NumPy, Matplotlib, Tableau	TensorFlow, PyTorch, Keras, Scikit-learn
Collaborate With	Works with data analysts, data engineers and business owners	Works with software developers, data engineers, and DevOps engineers
End Product	Business insights	AI/ML models, software in

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FAQs: AI Engineer vs Data Scientist: Key Differences

Who Is Better? An AI Engineer or a Data Scientist
Both the data scientist and the AI engineer play equally important roles in organizations. Whereas an artificial intelligence engineer works with other departments to build novel products that bring autonomy, a data scientist creates insights that foster profitable business decision making. So, both the roles are equally important for the organization

Who Earns More, Data Scientist or AI Engineer?
Both the data scientist and AI engineer earn comparable salaries. Although as per the latest insights from Glassdoor, entry-level AI engineers earn better base pay than Data Scientists. However, with experience, their salaries tend to become comparable.

Can AI Engineers Replace Data Scientists?
Given the technological advancements AI has been experiencing, an AI Engineer can automate a few tasks a data scientist does in probably a decade of time. However, AI is unlikely to replace data science completely. Data science involves business acumen, domain expertise, logical thinking and interpretive skills beyond the current scope of AI.

Is Data Science a Branch of Artificial Intelligence?
Data Science is not a branch of Artificial Intelligence, but the two fields are closely related and often overlap in skills and job responsibilities.

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AUTHOR

Nitin Grover

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AI Engineer v Data Scientist: Key Differences

Contents

Nitin Grover

Attend our Free Webinar on How to Nail Your Next Technical Interview

How to Nail your next Technical Interview

Worried About Failing Tech Interviews?

5 Key Software Engineering Manager Resume Skills

The Ultimate Machine Learning Cheatsheet: Top 20+ Key Terms and Concepts

Data Science Best Practices: Tips for Success

Top 7 Technical Challenges in Apple iOS Engineer Interviews

5 Factors That Affect Full Stack Developer Salary: Tips to Maximize Your Salary

Top 7 Preparation Strategies for Your First Job Interview

Top Python Scripting Interview Questions and Answers You Should Practice

Complex SQL Interview Questions for Interview Preparation

Zoox Software Engineer Interview Questions to Crack Your Tech Interview

Rubrik Interview Questions for Software Engineers

Top Advanced SQL Interview Questions and Answers

Twilio Interview Questions

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