How To Be Ready For The Top 3 Tech Jobs In The US For 2023-2024

How To Be Ready For The Top 3 Tech Jobs In The US For 2023-2024


As technology progresses and the job market evolves, it is important to stay ahead of the curve and be ready for the top three hot jobs in 2023-2024. The highest-paying jobs in the future are likely to be in fields such as artificial intelligence (AI), data science, and cybersecurity.

According to the “Future of Jobs Report 2023” by World Economic Forum, “Demand for AI and Machine Learning Specialists is expected to grow by 40%, or 1 million jobs, as the usage of AI and machine learning drives continued industry transformation.” The study also predicts a 30-35% increase (1.4 million) in demand for roles such as Data Analysts and Scientists, Big Data Specialists, Data Engineers etc. and a 31% increase in demand for Information-security Analysts.

To get a head start on these jobs, it is important to have a combination of technical and soft skills. Technical skills such as programming languages and data analysis are essential for most high-paying top jobs, while soft skills like creative thinking, communication, problem solving, leadership and positive attitude are also important for success. This blog post will discuss the recommended qualifications and skills that will help ensure that you are ready for these top 3 hot jobs.

Machine Learning Engineer: Machine learning engineers build and deploy machine learning models. They need expertise in algorithms, data structures, and programming languages. Recommended qualifications and skills that will help you prepare for it includes:

  • Bachelor’s degree in computer science, data science, mathematics, or advanced degrees or certifications from specialized programs in machine learning, artificial intelligence, or data engineering.
  • Proficiency in machine learning libraries and frameworks like TensorFlow, PyTorch, or scikit-learn.
  • Proficiency in programming languages such as Python or R.
  • Knowledge of statistical analysis and modeling techniques.
  • Strong programming skills for data manipulation and model implementation.
  • Understanding of cloud platforms and distributed computing.

Other jobs to look out for in this field include AI Research Scientist, AI Ethicist and AI Product Manager.

Data Scientist: Data scientists analyze and interpret complex data to uncover insights and solve business problems. They require a blend of statistical knowledge, programming skills, and domain expertise. Recommended qualifications and skills include:

  • Bachelor’s or an advanced degree in a field like computer science, mathematics, statistics, or a related discipline.
  • Proficiency in programming languages like Python or R.
  • Strong statistical and mathematical skills.
  • Experience with data visualization tools like Tableau or Matplotlib.
  • Knowledge of machine learning algorithms and techniques.
  • Familiarity with new technologies and cloud platforms like AWS, Google Cloud, or Azure for scalable data processing and machine learning capabilities.
  • Expertise in data cleaning, data manipulation, preprocessing, and feature engineering.

Other jobs to look out for in this field include Data Analyst, Data Engineer, Business Intelligence (BI) Developer and Data Architect.

Information-security Analyst: Information security analysts are highly skilled professionals who protect computer systems and networks from security threats, monitor for security breaches, conduct vulnerability assessments, investigate incidents, and develop and implement security measures.

According to the Economic Forum’s 2023 “Global Risks Report,” cybercrime and cyber insecurity are considered the top 10 global risk and yet there is an ongoing shortage of 3 million cybersecurity professionals around the world.

Therefore, demand for Information-security Analyst is expected to surge. Recommended qualifications and skills include:

  • Bachelor’s or advanced degree in cybersecurity or related field or industry-recognized certifications like Certified Information Systems Security Professional (CISSP) or Certified Information Security Manager (CISM).
  • Proficiency in operating systems (e.g., Windows, Linux) and networking concepts.
  • Proficiency in programming languages like Python, Java, or C/C++.
  • Good knowledge of security tools and technologies, such as firewalls, intrusion detection systems, vulnerability scanners, and encryption techniques.
  • Understanding of fundamental security principles, including risk management, threat intelligence, incident response, and security frameworks (e.g., NIST, ISO 27001).
  • Knowledge of the latest security threats, vulnerabilities, and attack techniques.

Other top jobs in cybersecurity include Chief Information Security Officer, Security Engineer, Ethical Hacker, Cybersecurity Consultant etc.

It is important to stay up to date with industry trends, develop new skills, and build a strong network that will help you find the right job. By using this information from Skywalk Global, you will be ready for any upcoming hot job opportunities in the present as well as in the future. Stay ahead and go for it!

(Shivangi Singh is a writer with Skywalk Global)


AI in Recruitment: Benefits and Drawbacks / AI in Recruitment: Pros and Cons

AI in Recruitment: Benefits and Drawbacks / AI in Recruitment: Pros and Cons

The use of artificial intelligence (AI) is rapidly advancing in various industries, from language-model chatbots like ChatGPT to personal assistants such as Alexa and Siri. The recruitment industry is no exception, as more recruiters are turning to AI to quickly find the best job applicants.

According to data, around 85% of recruiters believe that AI in recruitment can replace some parts of the hiring process. The reason is simple. AI can automate several aspects of the hiring process due to its ability to analyze vast amounts of data and identify patterns.

AI tools like applicant tracking systems (ATS) screen resumes and identify potential candidates. Also, these tools efficiently conduct mundane tasks such as crafting job descriptions, creating interview questions, writing Boolean search strings, scheduling interviews, sending out emails, and conducting background checks.

AI can offer many benefits, but it is not without its drawbacks. Here are the top pros and cons suggested by Skywalk Global before using AI in the recruitment process.


Benefits of AI in Recruitment:


  1. Timesaving: One of the most significant advantages of using AI in recruitment is the timesaving aspect.
  • An ATS can automate many of the repetitive tasks in the hiring process, such as resume screening and candidate tracking.
  • Chatbots can be used to quickly engage with candidates, providing personalized and efficient communication throughout the hiring process.
  • Video interviewing tools can be utilized to understand candidate responses, body language, and facial expressions to identify the best-fit candidates.
  1. Unbiased hiring: AI can help eliminate bias in hiring decisions by focusing on objective data rather than subjective opinions. Algorithms can be trained, monitored, and tested to ignore information such as a candidate’s age, gender, or ethnicity, ensuring fair hiring practices.
  2. Better candidate matching: Traditional methods of candidate matching were based on keyword searches and basic qualifications, such as education and work experience. However, AI-powered candidate matching algorithms and predictive analytics tools go beyond these and analyze a range of factors, including assessment results, social media profiles, personality traits, and cultural fit.
  3. Beats competition: An organization that uses AI tools and automation for recruitment has an edge over its competitors. For example, an organization using AI turns 10-15 hours of searching through social media and job sites into a two-minute search across multiple platforms, which helps them outperform their competition. Some recommended AI recruiting software includes Paradox, Fetcher, Amazing Hiring, Arya, Humanly, Textio, Seekout, hireEZ, eightfold, HireVue, and ChatGPT.


Drawbacks of AI in Recruitment:

  1. Lacks human touch: While AI can offer many benefits, it may lack the human touch essential for recruitment. Some candidates may prefer to interact with a human recruiter rather than a chatbot or automated system. Some may not feel uncomfortable sharing personal data with a machine. Human judgments are always needed to build relationships and also while interviewing and selecting which candidate would be the best fit.
  2. Bias in algorithms: Despite the potential for unbiased hiring decisions, AI algorithms can still be biased. Some critics feel AI could make employment discrimination worse through “institutional and systemic” biases. They believe that many of these algorithms are considered “black boxes” because they are not transparent about how they make decisions. They may be trained on biased data, leading to unethical and discriminatory hiring practices.
  3. Inadequate understanding of context: AI algorithms can struggle to understand the context of a candidate’s experience or qualifications, leading to incorrect assessments. It could work with insufficient data, which can result in qualified candidates being overlooked or unqualified candidates being selected. For example, a job seeker may use a different keyword for a job skill. If the AI does not have enough data to recognize that the skill could be transferable, it may miss out on a good candidate.
  4. Extra expense: Implementing AI in recruitment can be expensive, especially for small organizations. This can be a barrier to entry for organizations that may benefit from AI but cannot afford the expense.
  5. Data security risks: The use of AI in recruitment often involves collecting and storing huge amounts of personal data about job applicants. This data can be vulnerable to security breaches or hacking, that may compromise the privacy of job applicants and lead to identity theft or fraud.

Organizations should carefully consider these benefits and drawbacks before implementing AI in recruitment and ensure that they are using it ethically and responsibly. By doing so, they can improve their recruitment processes and find the best talent for their organization.