Data science vs artificial intelligence: skills and career opportunities

According to the report of international data corporation IDC, artificial intelligence technologies will hit the market by $97.9 billion by the end of 2023. According to the report of Garter, 80% of technologies were merged into the AI foundation by the end of 2021. In LinkedIn’s emerging job report, Therefore,  in 2020 data science and artificial intelligence had made a strong show by being on the top emerging job roles with the rate of 74% annual growth in the past 4 years (Gupta, 2021).

These statistics mean that the growth in implementing AI is increasingly demanding for the skills needed to make it successful. Data science and artificial intelligence are putting down the era of post-pandemic by rewarding perks and lucrative paychecks. Undoubtedly, data science and artificial intelligence engineers are seen with more respect than other sectors due to the world’s fastest-growing remote jobs that are crucial for the development of intelligent software services and products. Data science and artificial intelligence are two different job roles that are sometimes interchangeable due to their same skill set.

1. Table of Contents

   Data scientist vs artificial intelligence engineer: the basic difference

What is a data scientist

A data scientist is meant to utilize algorithms with the help of math, statistics, communication, design, engineering, and management skills to produce a meaningful and actionable program from a large amount of data that will give a positive impact on the business. Data scientists use visualization tools, statistical methods, distributed architecture, and data-oriented technologies such as python, SQL, Hadoop, R, Spark to obtain understanding from the data. The information gained by data scientists is meant to guide the various business processes such as analyzing user metrics, assessing market trends, predicting potential risks on business to make decisions that will help to achieve the company’s goals.

What is an artificial intelligence engineer?

From inventing speech recognition programs to developing robot hands to solving Rubik’s cube to plagiarism checker UK are all done by a one-man army that is an artificial intelligence engineer who employs the human mind into machines. An artificial intelligence engineer is the one producing intelligent autonomous systems and embedding them into applications. To build, maintain and implement end-to-end AI solutions, AI engineers are meant to use deep learning algorithms, machine learning, neural networks, software engineering principles, and NLP. The work theme of an AI engineer is to collaborate with businesses to deploy an AI system in the company to improve the operations, product development, and service delivery for a business’s profitability.

In some organizations, an AI engineer is more likely to work on a research basis to find the right model for solving a task. An AI engineer works along with architecture, business analysts, and data scientists to make sure the company’s goals are collaborating with the back-end analytics or not.

1. Data scientist vs artificial intelligence engineer: Skills

Data scientist

• Statistics and mathematics.
• Deep drive big data tools such as Hadoop, Spark, Pig, and Hive.
• Database tools such as SQL and other rational databases.
• Programming in R and Python.
• Extensive understanding of data management, data cleansing, and data mining.
• Uses data visualization tools that are Tableau and QlikView.

Artificial intelligence

• Data evaluation.
• Mathematical algorithms.
• Proficiency in Python and R.
• In-depth understanding of software engineering and computer science.
• Hands-on over Unix and Linux environments.
• Command over Deep learning, NLP, machine learning, computer vision, neural networks structure, and machine learning image processing.

The tech industry is struggling to get the best expert in the field of Artificial intelligence and data science. However, the job market is rising, & professionals suggest becoming proficient in both of the fields. For doing so, get a certification in artificial intelligence and data science. You can choose any one of these fields that fit best for you. The amount of learning and hard work goes on both of them, moreover, buy essay online for assistance if you are having difficulty in understanding any topic.

1. Data scientist vs artificial intelligence engineer: Who earns better

According to PayScale, an artificial intelligence engineer earns USD 122,793 per year. While data scientist salary ranges from USD 96k to 134k along with years of experience, job location, and level of expertise (Christopher, 2020).

1. Data scientist vs artificial intelligence engineer: Career path starts from here

If you are planning to pursue your career and deciding whether AI or Data science is the better option for your career then you will need to look for what your career goals are? What matches your competencies, expands your knowledge, and helps your business to move into a new direction of digital transformation.

If you are confused about where to start, then tell you one thing: both AI and data science are similar by means of skills and knowledge that are: Mathematics, Statistics, and programming. These three are the basic foundation of both fields either data science or artificial intelligence career pathways (Loon, 2022).

Artificial intelligence

Start by exploring different AI learning courses. If something attracts you, start looking for more AI-related courses such as coding, programming, algorithms, data modelling, and visualization.

Data scientist

However, If you are more interested in analytics and business learning then data science will be your educational pathway. Start by shaping your skills in data modelling, data mining, database management, wrangling, and programmings like R and Python.

In the nutshell

According to the report of World Economic Forums, at the end of 2020, there were 58 million new jobs. And AI is the topmost in-demand job in the job market. Don’t forget, the world needs data scientists to shrink the data to eliminate the technology gaps. In conclusion, Both have their own impotance in different domains. However, AI had some edge in terms of the future of the job market. Still, it is too early to say because the technology trends shift day by day.