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Do not let yourself down if you think you can not get AI-based jobs because of your lack of knowledge in coding. Yes, it is true that coding is needed in many data science jobs. Yes, it is true that when you aim to join a data science team that develops new applications, you need to code. But there are several companies and positions out there where people in various data science roles can join, and not all require to be perfect in coding. Here are the top 10 AI-based jobs that you should apply for even if you have zero knowledge in coding.
Technology projects have a lot of nitty-gritty to supervise and manage. One of the most popular AI-based jobs, the IT project manager will have to keep an eye on the progress of the project. They monitor the project from start to finish, ensuring that no details are lost in the project. IIT project managers don't have to do programming tasks themselves, but they do need to know the basics of what's happening on the technical side of the project. In addition, the manager must build skills to communicate critical and technical parts of the project to the client. These skills are essential for the smooth functioning of the organization.
IT support specialists facilitate clients' and customers' setup. Such AI-based jobs let you learn to use new software, equipment and troubleshoot any errors. The main work involves extensive programs and technical equipment, but you won't be required to code software programs. This role is a blend of technological know-how and customer support. So, you should have the basic technical skills needed for diagnosing and resolving project issues.
Websites, applications, and other technology-related designs are more than just looking good on the Internet. UX stands for user experience and the term "user experience" relates to how end-users interact with a product. Popular among AI-based jobs, UX designers follow basic standards to ensure that consumers can quickly browse their products and obtain the information they need. They perform in-depth research to understand the customer's needs and pain points to create a product that meets their requirements.
Software quality testers (SQTs) guarantee that software products are high quality before being released to the public. This field of AI-based jobs is connected to quality assurance but distinct from its quality assurance.
An SEO specialist, or a search engine optimization specialist, is usually classified under the technical domain. However, while search engine optimization (SEO) is sometimes lumped in with marketing, it has its own set of technical characteristics, such as dealing with growth rankings in search engines whose algorithms are constantly being tweaked. SEO experts work with developers and web designers to ensure that SEO best practices are followed across the board.
Most companies even struggle with starting the data and data science journey. They need education about the possibilities and business advantages of data. Companies need support in answering data science-related questions and setting up the vision and implementation roadmap. They require assistance in building capabilities and help in assessing tools and providers. A data science strategy consultant develops solutions for all these questions. This type of AI-based job will help you build up the full knowledge of a data scientist, as well as strategy and organizational expertise. But you do not need to code.
The data science process involves many proprietary software and platforms: master data management systems, analytics platforms, or visualization and BI tools. And someone needs to familiarize the user with all the technical functionalities and the usage possibilities. The job of a technical writer is demanding. They need to understand software and data science. They work with the developers, users, and marketing. It is not only the content that has to be developed and must be correct but also the design should be in place; and finally, legal requirements should be met.
Large organizations have specialized recruiters for the technology, AI, and data science positions. These recruiters need to understand the fundamentals of the data science job and processes, the applications, and goals. In addition, they need a lot of empathy and good communication skills. These recruiters have in-depth knowledge of data science and can detect flaws in CVs or made-up skills and experience.
Data science people are not necessarily good project managers. So, especially in large projects or projects that are part of a business transformation, a project manager must overlook the whole project and coordinate all involved stakeholders. Among such AI-based jobs, data science project manager plans, design, and execute data science solutions. You measure the progress of the project and assess the risks. When issues arise, you must escalate and solve them. And you have to ensure that the right people are on the project.
In the business environment, data science results need to be presented or are part of a report. The audience is business people with only a little knowledge in data science. Setting up relevant and understandable reporting with data visualization that tells non-technical people the whole story, is an art. So, in all data science teams of larger corporations, you find specialized people responsible for developing and maintaining proper reporting and visualization. You do not need coding experience for these tools even though you are developing dashboards, visualizations, and BI reporting. But you need the data science knowledge to get the communication and messages right into reporting.
