Access to Junior
At WorkMotion, we are at the forefront of helping companies manage local compliance regulations for remote employees in over 160 countries. Since the pandemic began, we have witnessed a rapid increase of workers worldwide embracing the opportunity to work from anywhere, as well as a rise in competitive, foreign location-based salaries available to the best global talent. Despite this extraordinary opportunity for economic growth, most governments have done little to capitalise upon the opportunity.
In order to adapt and remain competitive in the future global employment market, it is essential that cities adequately equip their local talent to work the jobs of tomorrow. As such, cities need to cultivate an English-speaking, tech-savvy workforce through education and develop proper infrastructure for remote workers through affordable coworking spaces. Crucially, governments must legislate forward-thinking compliance procedures to ensure it is easy for foreign companies to manage local employees. At WorkMotion, we are involved in this radical shift, which is why we decided to undertake this study - to understand which cities are best placed to compete for the remote jobs of today and tomorrow, and benefit from the increase in taxable income that will be generated.
For the study, we analysed six professions in which remote work is rapidly becoming more common. We first considered the access to talent in each city and, to reflect the need for remote workers at different skill levels, we ranked the concentration of junior and senior-level talent as a score.
Next, to assess which cities are leading the way in facilitating their local population to work remotely, we studied each city’s remote working infrastructure. To do this, we considered the national ease of compliance regulation for foreign companies hiring locally as well as the number of coworking spaces in each location that enable comfortable remote work. Given that English is the predominant language for global business and will be a necessity for remote workers of the future, we also ranked cities’ English proficiency levels.
Lastly, we compared cities’ salaries for each profession from the perspective of location-based pay. This was important as, in the new normal of remote work societies, workers will increasingly be able to choose where their talent is best remunerated without having to relocate. Therefore, the better the quality of the local talent, the more competitive the city will be, attracting the highest-paid global opportunities.
“The new normal constitutes a radical change in cities’ priorities, given that local talent is now the fastest and most effective means for economic growth,” comments Carsten Lebtig, Co-Founder and Managing Director of WorkMotion. “Cities with a competitive workforce will now have access to the economic benefits of high-paid jobs through taxation, without having to create them locally.”
The resultant overall rankings are split between junior and senior talent in each industry and reflect the access to talent, average local salaries and remote working infrastructure in each city, revealing how competitive their talent is compared to the global employment market.
Access to Junior
Access to Senior
Deviation from Average
Salary in Top 25 GDP
Average Local Junior
Average Local Senior
Ease of Compliance
Number of Coworking
Overall Junior Talent
Overall Senior Talent
You can select any of the 6 careers analysed in the study and sort each factor from highest to lowest and vice versa by clicking on the icon
above each column.
The Local Talent Index uses data to identify the most competitive global cities for remote working positions based on Access to Talent, Local Salaries and Remote Work Infrastructure. The results provide a detailed analysis of the employment market in each location, with a focus on individual industries.
The study was divided into four main categories: Access to Talent, Local Salaries, Remote Working Infrastructure and Overall Ranking.
The study considered these factors in relation to the following occupations:
Data was collected from over 200 cities around the world. After an initial review of all the indicators and their availability, 100 cities were shortlisted based on the reliability and comparability of data. Further iterations of the study will add countries as data becomes available.
A score that reflects the number of local graduates available in each city for each occupation. All the indicators are expressed as a score altogether, with a higher score indicating that the city has a higher number of graduates per occupation. It comprises the following indicators:
This indicator comprises an estimate of the number of graduates from top universities in each city, identified using global university ranking lists. Using the total number of students for each university and data collected on the number of students per faculty from individual university portals where available, the number of graduates for each university was estimated within the major faculties of Arts and Design, Engineering, Computer and Information Technology, Arts and Humanities, Social Sciences and Management, Natural Sciences, and Life Sciences. Faculties per occupation were assigned as follows:
The number of universities per city. University addresses were extracted from global university directories and lat-longs were utilised to assign these addresses to the city selection.
This indicator provides a ranking of cities according to the level of English proficiency. Where the city-level ranking was unavailable, the country-level ranking was used. English-speaking cities and cities with high proficiency were taken at the
base level while cities with moderate or limited proficiency were penalised accordingly.
A score that reflects the local professionals available in each city for each occupation. All the indicators are expressed as a combined score, with a higher score indicating that the city has a higher number of professionals per occupation. It comprises the following indicators:
This indicator comprises an estimate of employees available for each occupation in each city. For the US, annual data published by the US Bureau of Labor Statistics was used, which provided a comprehensive breakdown of occupations by Metropolitan Statistical Area.
For most cities in Europe, EUROSTAT provides data on employment broken down by industry. A profile was created for the distribution of occupations within each industry based on detailed occupation-by-industry datasets from the US Bureau of Labour Statistics. The Eurostat industry data combined with the industry occupation profiles were used to model the number of employees in each occupation on a city level.
In non-EU areas where geographically detailed data was scarce, national employment data per industry was collected from national statistical departments, as well as from OECD and ILO, which combined with occupation-by-industry profiles to form an estimate of the total number of persons employed in each occupation at a national level. Data from company directories was used to approximate the spread of these occupations across cities.
In countries where industry-level data was unavailable, the total number of employed persons was calculated as an estimate. Regression analysis was then undertaken based on the data from national statistics and online directories to arrive at an estimate.
To normalise for population, the per capita estimate for the employee pool was included.
In order to estimate the number of companies operating in each city, data from company directories was collected. The database was filtered to include companies active from 1900 to 2022, with a total of 441,914 companies retrieved, providing an estimated range of employees. The average number of employees per company was calculated, then multiplied by the percentage each industry was assigned based on available sources.
The interactive nature of this occupation merits the inclusion of English language proficiency as an indicator at a senior level. This factor provided a ranking of cities according to the level of English proficiency. Where the city-level ranking was unavailable, the country-level ranking was used. English-speaking cities and cities with high proficiency were taken as the base level while cities with moderate or bad proficiency were penalised accordingly.
The study examined salaries offered for each occupation in cities within the top 25 highest GDP bracket. Countries with fewer than one million inhabitants were not included in this list; this includes, Monaco, the Bahamas, Liechtenstein, Luxembourg, Bermuda, the Isle of Man, the Cayman Islands, Macao SAR China, Iceland, the Faroe Islands, Greenland, San Marino, Andorra, Guam, US Virgin Islands, New Caledonia, Puerto Rico and Sint Maarten. The third quartile salary for a profession in each city was compared to these highest-paid cities. A deviation of +25% indicates that the city offers salaries that are 25% higher than the top 25 salaries. Similarly, a deviation of -25% indicates a salary that is 25% lower than the top 25 salaries for that profession.
The average salaries at junior and senior levels in each country and city for each occupation.
A score that reflects the ease of employment compliance in each city, taking into account national compliance policy, labour policy, local governance and taxation.
The total number of coworking spaces available in each city.
A score that reflects the levels of English proficiency in each city. Where city-level rankings were unavailable, country-level rankings were applied. English-speaking cities were taken as a base level, while cities with moderate or high proficiency in English were ranked accordingly. A higher score indicates a greater degree of English proficiency.
A score that reflects the overall rank of each city’s junior talent, comprising all indicators related to junior talent within the categories of access to talent, local salaries and remote working infrastructure.
A score that reflects the overall rank of the city’s senior talent, comprising all indicators related to senior talent within the categories of access to talent, local salaries and remote working infrastructure.