Site logo
in-demand skills

Top Five In-Demand Skills in the US

By April 18, 2022 News

The most in-demand skills in the USA right now include:

  • Full-stack development
  • Cybersecurity
  • Artificial Intelligence (AI)
  • Data Analytics
  • Data Science

Read on to know more about these skills.

1. Full-stack developer

Full-stack developers work on applications’ back (server) and front (client) sides. To become a full-stack developer, an individual must be skilled in various coding niches that include graphic design, UI/UX management, and databases.

The responsibilities of a full stack developer are likely to include the following:

  • Assistance with software development and design
  • Being up-to-date with the latest technological advances for optimizing software
  • Ensuring responsive application design
  • Designing new app features in collaboration with graphic designers
  • Optimizing software through repeated tests and debugging
  • Writing code for both the software’s front and back ends

2. Cybersecurity specialist

Cybersecurity specialists are responsible for protecting an organization’s IT infrastructure. From monitoring the potential threat of cyber attacks to mitigating them if they take place and preventing data breaches – a cybersecurity specialist may have to play multiple roles.

A cybersecurity specialist’s responsibilities include:

  • Monitoring the performance of applications and networks to detect irregularities
  • Deploying detection and prevention tools for dealing with cyberattacks
  • Setting up a business continuity/disaster recovery plan in collaboration with IT operations
  • Automatically updating applications by setting up patch management systems
  • Performing regular audits for ensuring compliance of cybersecurity practices
  • Implementing vulnerability management systems for both on-premises and in-cloud assets

3. Artificial Intelligence (AI) specialist

Since 2016, no other skill has been more in-demand in the USA. AI specialists have expertise in artificial intelligence (AI) and machine learning (ML), and may be required to assume various responsibilities depending on the needs of organizations.

Typically, AI specialists are responsible for the following:

  • Designing innovative computer systems that can perform a variety of functions such as fingerprint recognition and voice recognition
  • Creating and implementing chatbots and other AI-powered services
  • Configuring evolutionary AI and deep learning for streamlining and automating operations across industries
  • Solving research and/or business problems through text and/or image recognition and natural language processing (NLP)
  • Retrieving crucial information and managing databases

4. Data Analyst

Data analysts work across a multitude of industries, and their primary jobs involve the collection, cleaning, and interpretation of data sets for solving problems and/or answering questions. They also help stakeholders in a business to understand data, which allows the stakeholders to make major business decisions going forward.

The responsibilities of a data analyst include:

  • Using automated software and tools for data extraction from various sources
  • Assessing data quality by performing a thorough analysis
  • Fixing coding errors and removing corrupt data
  • Analysis of trends on local, national and global levels for understanding impacts on the organization and the overarching industry
  • Preparing reports that state predictions and existing patterns and trends
  • Facilitating the assessment and comparison of business functions through the assignment of a numerical value to them

5. Data scientist

Data scientists are similar to data analysts. However, the roles have certain distinctions. Typically, data scientists are responsible for creating predictive models and algorithms for data extraction and designing data modeling processes.

A data scientist’s responsibilities are:

  • Acquiring, cleaning, and processing data
  • Storing and integrating data
  • Analyzing and investigating data
  • Applying artificial intelligence (AI), machine learning (ML), statistical modeling and other data science techniques
  • Measuring results and improving them
We use cookies to improve your experience on our website. By browsing this website, you agree to our privacy policy.

Sign in

Sign Up

Forgot Password

Job Quick Search