Digital Marketing Specialist: Career Paths and Opportunities in the USA

Skill categories. LinkedIn allocates standardized skills into two categories: tech/digital skills and disruptive tech/digital skills. Tech/digital skills use digital devices, communication applications, and networks to access and manage information. They enable people to create and share digital content, communicate and collaborate, and solve problems. Examples 

from basic digital literacy to web development. Disruptive tech/digital skills are used to develop new technologies that are expected to affect labor markets in the coming years, notably artificial intelligence, robotics, and genetic engineering. In this report, disruptive tech/digital skills are referred to as advanced disruptive digital skills. The current study further 

subdivided tech/digital skills into basic digital skills and intermediate digital skills. Basic digital skills are those fundamentally required to understand simple tech concepts and use enterprise technologies, platforms, and solutions on the job. Intermediate digital skills enable those who master them to deploy hardware and software to build tools, platforms, and 

Applications that can be easily used

by others with only basic digital skills. Thus, the three skill groups in the current ADB–LinkedIn study are  basic digital skills,  intermediate digital skills, and (iii) advanced disruptive digital skills. Table A1 shows examples of each category. (The ADB–Outline credential survey ranked digital skills in four categories by dividing intermediate into two categories [footnote  Hiring events. A job hiring was deemed to have occurred when a LinkedIn member profile 

indicated a change of employer. Aggregating individual digital hires enabled researchers to compare them in a given period with the same period in the previous year, yielding change in the hiring rate year on year for each of the three categories of digital skills: basic, intermediate, and advanced disruptive. Among hires, one who had at least one basic skill 

counted as a basic hire, one who had at least one intermediate skill was an intermediate hire, and one who had at least one advanced disruptive skill was an advanced disruptive hire. In short, LinkedIn members with skills across multiple categories were tagged for their highest skill category. The data, thus generated, enabled research methodologies to determine the following: Change in the digital hiring rate in Asia and the Pacific versus the United States 

The digital hiring rate is the proportion 

of LinkedImembrs who list digital skills in their profile and indicate a change in employer that month. Change in the rate is measured here year over year. Differences in the average share of digital hires by skill category in 2020 (Table 1). Hires in each category were aggregated in each month of 2020 and indexed against January 2020 to create a time series depicting the hiring trend across 2020. Jobs most in demand and fastest-growing jobs 

The top jobs in demand were the job titles most commonly reported by LinkedIn members hired in each country in two 6-month time frames: (i) from 1 September 2019 to 28 February 2020 and (ii) from 1 September 2020 to 28 February 2021. These time frames allowed comparisons year on year but left out March–August 2020, a period of severe lockdowns and hiring freezes. The first period was thus before the pandemic and the second after the 

pandemic or at least after the worst of it in terms of economic disruptionalue from consuming is either lacking or weak. The related experience did not generate emotional value, according the results. Regarding social events, particularly within the theme park, respondents do not see their trips to Winter Wonderland strengthening their relationships with others. For many 

People nowadays sharing virtually experiences 

via social networking is more crucial than living them in the entertainment venue.cofounding, as were internal transfers or role changes within a company, as they may reflect internal restructuring, not job market demand. To better capture only job movements in the labor market, unpaid positions, internships, and student roles were excluded. Top unique representative digital skills needed for top jobs in demand (Table 4). This was researched by 

mapping the “skill genome” of each job to highlight the unique skills it required. Unique skills were extracted by applying a weighting scheme analogous to term frequency–inverse document frequency (TF–IDF), a commonly used data-mining technique for textual analysis. This step was necessary because a set of generic and commonly held skills can often 

obscure the unique skills needed for a specific job. For example, data scientists frequently include in their LinkedIn profiles Microsoft Word and Microsoft Excel, but these are among the most commonly cited digital skills across categories and therefore do not distinguish data scientist from other jobs. To extract unique skills, each skill had a weighted score for each members were to add it to their profile, compared with the likelihood of that skill being 

Conclusion

members add the skill across a wide range of jobs, the lower its weight. Based on the skills genome of each of the jobs in top demand, occurrences of each digital skill were counted, and the most frequent were included among the skills most in demand. Links between employees in jobs in demand and their fields of study (Table 5). Based on jobs in demand as identified in Table 2, employees currently in those jobs were identified and their 

university fields of study were noted. Company placement in an industry (digital skill demand in three emerging industries). To identify which companies in the seven countries covered in this report were in e-learning, renewable energy, or smart cities, researchers looked at each company’s self-declared industry, company description, and company business 

keywords. Where possible, keywords from job postings were also used, but with filters applied to ensure high-quality outputs: To ensure that the job was in one of the company’s core business lines, keywords had to appear in more than 15% of its job postings, and the company had to have posted at least five jobs with these keywords since 2017. Analysis 

classified over 21,000 companies in e-learning, 2,500 in smart cities, and 13,000 in renewable energy. Relative growth in company numbers by industry (Figure 8). The proportion of new companies in a specific industry is the number of new companies in that industry divided by the number of new companies in the country. A company’s founding year was as reported on its LinkedIn page or, failing that, inferred from the earliest date an employee could be

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