Top AI jobs in 2024

1. Data Scientist

AI & Data Science opportunities and AI & Analytics careers are a hot topic at the moment. Data Scientists extract, analyze, and interpret large amounts of data using a series of tools, from statistical and algorithmic to AI and Machine Learning. In a nutshell, they turn raw data into meaningful insights that companies can use to improve their work. 

In the age of AI, Data Scientists can use Artificial Intelligence to build algorithms, design experiments, interrogate data, create reports, and more.

If you're looking for a certification that can attest your expertise as a Data Scientist, you may be interested in Microsoft Azure Data Engineer Associate (DP-203) or Microsoft Power BI Data Analyst Associate (PL-300); if your role encompasses Data Protection too, you may want to look into the Certified Data Protection Officer (CDPO) certification from PECB.

2. Software Engineer

Sometimes called Software Developers, Software Engineers use programming languages to create software and apps; they also test, maintain, and improve them.

In 2024, AI-powered testing tools can generate test cases automatically, execute tests across various scenarios, and analyze test results in real time, enhancing the coverage and accuracy of such tests.

Depending on the tech stack your company is using, you can attest your skills by passing an official Microsoft certification such as the Microsoft Azure Developer Associate (AZ-204), Microsoft Power Platform Developer Associate (PL-400). Microsoft is at the forefront of AI innovation, even introducing a new laptop keyboard to mark 2024 as "the year of the AI PC," so it's expected that updates to these courses, which are frequent, will introduce AI concepts soon.

(Pro tip: Find out how you can get unlimited Microsoft training.) 

3. Robotics Engineer

Robotics has been a fascinating field for decades, combining elements of mechanical and electrical engineering with computer science. Its machines innovate the automotive industry, manufacturing, healthcare, national defense, and more. 

In the age of AI, Robotics Engineers build and maintain AI-powered robots. AI can assist them in designing these robots, testing prototypes, and fixing faults. According to the UK Government, this job could help the environment by developing sustainable technology.

To succeed in this highly specialised career, it is recommended that you have a strong background in Computer Science, such as a university degree; further certifications such as this BCS Foundation Award in Smart Products, Robotics, and Automation, can give your CV an edge.

4. AI Product Manager

If you have experience in Product Management and understand how AI products are built, you could specialise in AI. Artificial Intelligence is highly complex; however, it is still a product and, as Product Manager, you need to ensure it can be monetized and used to grow your company according to its vision.

Aside from this, in the age of AI, you can incorporate Artificial Intelligence productivity tools in your workflow to become more productive; for example, the latest ProdPad has integrated ChatGPT. 

You will still need to put together business cases, working with Data Scientists, do problem mapping, and have excellent communication skills. According to ProductPlan, "Some AI experts describe AI PMs as translators because they must bridge the language of Data Science with the language of Product Development."

If this sounds interesting to you, you could try Scrum.org's Scrum Product Owner™ (PSPO I) or the BCS Practitioner Certificate in Digital Product Management; if you're more interested in planning and inventory management, this ASCM certification could help attest your skills.

5. AI Researcher

The rapid expansion of AI is built on theoretical and experimental research. In 2024, AI Researchers will continue to push the boundaries of what is possible.

To become an AI Researcher, you need a degree in a related field (e.g., Computer Information Science), and a deep understanding of AI, Machine Learning, as well as Software Development, Data Science, Robotics, and similar topics. As AI is expected to impact nearly every industry in the coming years, this job will be in increasing demand.

AI Researchers need to be fluent in multiple programming languages, such as Python and R, have strong math skills, such as calculating algorithms, statistics, calculus, linear algebra, and numerical analysis, and be able to manage data, as a typical workday will involve handling large amounts through software such as Spark or Hadoop.

To achieve this, you may be interested in courses such as Python Programming, the Artificial Intelligence (AI) Developer™ certification developed by Blockchain Council, or or the well-known Data+ by CompTIA.

6. AI Applications Analyst

Specialising in languages such as Java, Oracle, SQL, or UNIX, Application Analysts administer, monitor, and maintain software infrastructures and applications. Working closely with Application Developers and Software Engineers, they ensure that critical business processes run smoothly and that data and applications are safe.

In 2024, the rapid expansion of AI will save time through automation (for example, routine system backups and upgrades, installing new OS, monitoring requests), but may also pose increased security risks. What can you do to prepare?

To refresh your programming knowledge, you may be interested in courses such as Python Programming or the AI Developer™ or Expert™ certifications developed by Blockchain Council. For Cyber Security, you could consider CertNexus Cyber Secure Coder (CSC) or CompTIA Security+.

7. AI Engineer

AI Engineers develop tools, systems, and processes that use AI to solve real-world problems. These AI solutions can increase productivity and cut costs across a variety of industries, from retail and marketing to healthcare, education, and government.

To upskill as an AI Engineer, you need a strong background in AI, Machine Learning algorithms, and Data Science; usually, you need a university degree. To attest your multi-faceted skills, you could explore Deep Learning through courses such as Intro to TensorFlow and the HP Deep Learning Theory and Practice; depending on your tech stack, training in Microsoft Azure, such as the Azure AI Engineer Associate (AI-102) could help you stand out.

(Pro tip: At Firebrand, we are a Microsoft Cloud Partner for Data and AI, so your training is in safe hands!)

8. AI Developer

Artificial Intelligence Developers integrate AI functionality into software. Similar to NLP Engineers (see number 10), they design, develop, implement and monitor AI systems in IT products such as smart assistants and chatbots.

Successful AI Developers are skilled in programming languages such as Python, Java and Scala, Deep Learning, coding, Cloud Computing, and various profiling and analytical tools; in addition, they are excellent communicators.

If you're interested in this, you may consider becoming certified in developing apps for Android and iOS, Python Programming, or head straight to an AI Developer certification such as the Blockchain Council AI Developer™.

9. AI Data Engineer

While Data Scientists (see number 1) extract, analyse, and interpret big data for insights, Data Engineers develop the architecture that allows the Data Science team to access this data.

Data Engineers create data pipelines by using programming languages such as Java, Scala, C++, or Python; experienced in data mining, data migration, and data visualisation, they build systems that collect, manage, and convert raw data into usable information. In the age of AI, depending on the company, Artificial Intelligence is integrated into this process at various stages, including data collection.

If you're interested in this, a Data certification in the context of Cloud Computing could help you stand out: the Microsoft Azure Data Engineer Associate (DP-203), Google Cloud Fundamentals: Big Data and Machine Learning, or the Microsoft Cloud Workshop on Big Data & Visualisation are solid options.

10. NLP Engineer

If you have a linguistics background such as Computational Linguistics, Natural Language Processing (NLP) for AI could be a great option.

NLP Engineers develop sophisticated software that understands human language; voice assistants such as Amazon Alexa or Apple Siri, speech recognition software, and similar tools have become widespread in recent years.

To achieve this, NLP Engineers need skills such as semantic extraction, modelling, n-grams, a bag of words, sentiment analysis, as well as experience with Python and ElasticSearch, among other specialised skills.

If you're interested in ChatGPT, you could become certified by taking a course such as the Blockchain Council ChatGPT Expert™ or the OpenAI/ChatGPT Embedding and Development within Microsoft. Microsoft and Amazon AWS also offer interesting courses about Deep Learning: Cognitive Services and Deep Learning and Deep Learning on AWS.

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