Career in Artificial Intelligence

Artificial intelligence is at the heart of the current technological revolution, and it’s only growing smarter. It is everywhere, even in places where you might not expect it. The power of AI can be found everywhere, from music preferences to home appliances and healthcare.
AI, the brains behind computer vision, speech analysis, and natural language processing, has a wide range of effects on industry and society.

It’s no surprise, however, that the AI area is brimming with job openings — so many, in fact, that the industry is currently confronted with a unique problem: there are too many positions and too few competent individuals. On the plus side, it implies that for those with the skills, employment is nearly guaranteed and is well-paid.
But what all skills do an AI professional need?

What Skills Does an AI Professional Require?

If you really want to work in artificial intelligence, be sure you have the skills that will set you apart from the competition and help you find the perfect position. First and foremost, calculus and linear algebra skills are critical. You should also be familiar with and have some expertise with programming languages such as C, C++, or Python.
The ability to communicate, Goals and methods for Digital Marketing, and Skills in the analysis are an add-on if you want to pursue AI in the future.

If you’re not already working in AI, the first step is to do some homework, which includes speaking with current AI specialists and looking into respected institutions and programs. According to Springboard, hiring managers will most likely require you to have a bachelor’s degree in math and a basic understanding of computer technology.

Undergraduate degrees in computer science or engineering are a good starting point, but a master’s degree in artificial intelligence can provide firsthand experience and knowledge from industry experts, which can help you land a job and set yourself apart from the competition.

1. Proficiency with Unix Tools

Unix programs such as awk, cut, tr, search, and others are responsible for the majority of AI processing on Linux-based platforms. As a result, a programmer must understand how these tools work.

2. Data Science Efficiency

You should also be familiar with data science, as AI professionals utilize it to process massive volumes of data (big data) and derive meaningful information in a timely and systematic manner.

3. Up To Date With The Most Recent Fashion Trends

Every second counts in the realm of artificial intelligence. An AI professional should stay up to date on all industry news on a regular basis.
To improve his or her skills, one must join and actively participate in tech networks and forums. They can also benefit from online tutorials or courses.

4. You Should Be Curious And Inventive

Being inventive and inquisitive will aid you in solving challenges, as you will be able to solve them by employing unorthodox approaches.

5. Expertise in Machine Learning

As we all know, machine learning is a subset of artificial intelligence. You should be familiar with machine learning because it is used in cybersecurity and online fraud detection, as well as rapid analysis and prediction.

6. Robotics

We are moving towards a future that is more automated. And robotics will play a significant role in the automation process. Because robotics is the result of AI research, you should be well-versed in it.

7. Programming Languages Fundamentals

Accountancy is to a Chartered Accountant what programming languages are to an AI specialist. One of the most important talents for a career in artificial intelligence is the ability to code in C++, Python, Java, R, and other languages.

In this discipline, each language has its unique applications. R is used to create statistical software and do data analysis, whereas Python is used to quickly create complicated algorithms.

8. Algorithmic and Mathematical Understanding

You must have a strong understanding of applied mathematics and a set of algorithms to be a good AI candidate. Problem-solving and analytical skills will assist you in completing jobs more quickly. You should also have a basic understanding of statistics and probability. This aids in the comprehension of various AI models such as Naive Bayes, Gaussian Mixture Model, and others.

Career Opportunities in Artificial Intelligence

1. Business Intelligence Developer

What is the first thing that springs to mind when you hear the word “intelligent”? It’s likely that it might be the government intelligence organizations around the world or any support group. But when referring to the corporate sphere, intelligence is known by the name of business intelligence.

The phrase “business intelligence” refers to the various tactics and technologies used by businesses to give actionable data to end-users so that they can make informed business decisions.

Every company generates a massive amount of data from its day-to-day activities. These can come from both internal and external sources, including market research, sales numbers, corporate budgeting, and so on. A Business Intelligence developer, often known as a BI developer, is able to use software tools to transform data into usable insights that will have a significant impact on business decisions.

This post is open to anyone who is familiar with computer programming and data sets. A formal bachelor’s degree in computer science, mathematics, or engineering can help you get work. The problem-solving abilities and analytical abilities of the applicants should be exceptional.

2. Big Data Engineer

A big data engineer aids in the creation of an ecosystem that allows corporate systems to communicate with one another. They develop and manage a company’s big data, as well as achieve faster outcomes from big data, or large amounts of data.

A solid understanding of programming languages, primarily R, Java, Python, and C, is required to become a big data engineer. You should be able to develop large-scale applications and do data warehousing. It’s also beneficial if you know how to use Apache Spark and SQL.

3. Data Mining & Analyst

Data mining, also known as knowledge discovery in databases, is the nontrivial extraction of implicit, previously unknown, and potentially usable information from data in artificial intelligence and machine learning. In huge databases, statistical approaches are employed to identify patterns and other linkages.

The widespread availability of huge volumes of data, as well as the need to transform such data into valuable information and knowledge, has sparked interest in data mining. Risk monitoring, company management, manufacturing control, market analysis, engineering, and scientific discovery are all possible applications of the knowledge gathered.

4. Research Scientist

In applied mathematics, machine learning, and deep learning, a research scientist is an expert. You should be well-versed in reinforcement learning and natural language processing.

Most research scientists should have a Ph.D. in computer science or at least a master’s degree. A research scientist can make between 6 and 16 lacs per year.

5. AI & ML Developer/ Engineer

AI & ML engineers are problem solvers who create, test and implement various Artificial Intelligence and Machine Learning models. They have the ability to oversee AI infrastructure. They are in charge of statistical analysis, statistical testing, and statistical design. Also they focus on deep learning systems, machine learning methods, and neural networks in order to create usable AI models.

So, in a nutshell, they implement AI and machine learning-based solutions for the organization. You’ll require solid programming skills in Python, Scala, and Java to work as an AI and ML developer. You will have the opportunity to work with frameworks such as Azure ML Studio, Apache Hadoop, and others. If you stick to the set of AI engineer learning route, you’ll be successful!

6. Robotic Scientist

Influenced by global automation trends and the advent of robotics in the field of artificial intelligence, we can see that the need for robotics experts is on the rise. Robots are snatching the jobs of those who handle manual or repetitive & dull activities in today’s fast-paced society, where technology is becoming the pioneer. It is, on the contrary, employing robotics experts.

As a Robotic Scientist, you’ll be in charge of designing operating systems, validating operating functionalities, and estimating costs to mass-produce devices. You’ll create mechanical devices, such as robots, that will automate human-to-human tasks. A bachelor’s degree in robotics, mechanical engineering, or electrical engineering is required to work as a robotic scientist.

7. Software Engineer

Traditional computer science roles like software engineers are also used in the AI area to create the programs that artificial intelligence tools rely on.

They’re involved in the complete development and production of digital programs and systems. Individuals in these professions are responsible for designing the technical functionality of products that use machine learning to perform a variety of activities in the context of AI.

Software developers are expected to rise at a 22 percent annual pace by 2029, according to experts. They earn an average of $110,140 per year, with an opportunity for advancement for those with an AI specialization.

8. AI Data Analytics

Whether in the healthcare industry, banking industry, telecom sector, or any other field, AI Data analysts are recognized to have a significant impact.

Data mining, data cleansing, and data interpretation are the primary duties of a Data Analyst.

You must have a solid understanding of regression and be able to utilize MS Excel to be considered for this position. The main task is to cater to AI-oriented solutions and schemes to improve the services provided by a specific industry by studying the trends and patterns of specific datasets using data analyzing skills.

A bachelor’s degree in mathematics or computer science is required to work as an AI data analyst.

9. Data Scientist

Because of the increased need for data scientists, there’s a good chance you’ve heard of the term before. A data scientist’s responsibilities include recognizing valuable data streams and sources, collaborating with data engineers to automate data collection processes, dealing with big data, and analyzing massive amounts of data to discover patterns in order to develop predictive machine learning models.

Job seekers must be familiar with modern tools such as Spark, Hadoop, Pig, or Hive in order to pursue this career path. The applicants should be familiar with programming languages such as Python, SAS, R, Scala, and SQL.

10. Product Manager

Artificial intelligence plays a key role in the position of a product manager in today’s leading companies. A product manager’s job entails resolving difficult problems by systematically collecting data. You should be able to spot major business roadblocks and then gather related datasets for data analysis. After the data is interpreted, the product manager employs effective AI methodologies to assess the commercial implications of the conclusions produced from the data.

One must be proficient in programming languages such as Python, R, and SQL, as well as have a thorough understanding of AI-ML, computer science, statistics, and marketing-related key ideas. In the end, your income as a product manager is determined by your experience, talents, employer, and location.

11. User Experience

User experience responsibilities entail working with products, including those that incorporate artificial intelligence (AI), to ensure that customers understand their purpose and can use them easily.

Did you know that the Mac operating system was created out of a desire for a product that was more user-friendly and didn’t require sophisticated technical knowledge to run?

“The iPhone was all about the user experience,” explains the designer.

In the case of AI, a User Experience specialist’s tasks could include determining how humans engage with these technologies in order to design functionality that better meets those humans’ requirements in the future.

12. Natural Language Processing

The most widely used AI consumer applications center around language. AI techniques have been used to duplicate human speech in a number of contexts, from chatbots to virtual assistants to predictive messaging on smartphones.

To do so effectively, developers enlist the help of natural language processors—people who are fluent in both languages and technology and can aid in the development of these tools.

Individuals in these positions will use their in-depth knowledge of both language and technology to create systems that allow computers to successfully converse with humans.

Which Companies Employ AI Experts?

Being an AI expert is a prestigious position, but which firms actually hire for this position? Here’s a list of companies that hire AI experts:

• Accenture
• Jaguar Land Rover is a British automobile manufacturer.
• NVIDIA
• Amazon
• Microsoft
• Google\Facebook

Jobs in the AI field are rapidly expanding. While there are many job openings and prospects in the AI business, there is no denying that skilled personnel is in short supply. According to a report, AI has a high probability of creating around 58 million employees by 2022.

Conclusion

Artificial intelligence is a rich area with above-average job growth, but it is a cutthroat business. Roles in this field are extremely specialized, requiring a strong technical background as well as substantial hands-on experience. Those with this uncommon combination of talents and real-world experience will be able to land any number of AI jobs and continue to shape the field’s landscape for years to come.