FINTECH MANPOWER DEVELOPMENT IN ASIA-PACIFIC FINANCIAL CENTERS WITH A FOCUS ON ARTIFICIAL INTELLIGENCE AND BIG DATA PROFESSIONALS

49 48 Comparing the Artificial Intelligence and Big Data Manpower Ecosystem of the Six Asia Pacific Financial Centers Data Analyst Vice President Director Analyst Associate Business Analyst Co-founder Senior Business Analyst Founder Product Manager Project Manager Software Engineer Manager Assistant Vice President Chief Executive Officer Managing Director Senior Manager Associate Director Consultant Executive Director Senior Analyst Financial Advisor Senior Project Manager Quantitative Analyst Data Scientist Senior Software Engineer Account Manager General Manager Investment Manager Data Specialist Marketing Manager Analytics Manager Financial Analyst Senior Associate Investment Analyst Member Product Owner Senior Data Analyst Portfolio Manager Board Member Relationship Manager Assistant Manager Partner Chief Operating Officer Investment Banking Analyst Senior Product Manager Trader Intern Data Engineer Researcher Note. The results are based on aggregated data from all six financial centers. Figure 3.2 The Distribution of the Top 50 Job Titles of AI and Big Data Professionals in the Financial Services Sector 3.8 Job titles and skills analysis in the financial services industry In this section, we focus on the financial Service sector since it employs the largest proportion of AI and big data talent in each city (Table 3.4). We report the job title distribution and the associated top skills for each job title. We further aggregated the data over the six financial centers. Figure 3.2 depicts a bar chart showing the distribution of the top 50 job titles of AI and big data professionals. The most common job title is data analyst with more than 1,000 AI and big data professionals associated with this title. Table 3.10 shows the top five skills associated with each job title. Other than data analysis, knowledge in banking and finance are also very common and important business-related skills. Regarding technical skills, the top skills are data analysis, followed by programming languages including SQL and Python. Apart from that, we also calculated the talent flow between finance and other industries for each financial center as shown in Table 3.9. We observed that there are generally more inflows from non- finance to the finance industry for all cities, and the net inflow of talent from non-finance to finance is the largest in Hong Kong with a ratio of 2:1, followed by Sydney with a ratio of 1.96:1 during the period. Table 3.9 The Talent Flow of AI and Big Data Professionals between Finance and Other Industries Talent Flow Hong Kong Singapore Tokyo Shanghai Shenzhen Sydney From Non-Finance to Finance 1,222 2,510 215 770 157 3,259 From Finance to Non-Finance 611 1,598 148 508 118 1,666 Net Inflow Ratio 2:1 1.57:1 1.45:1 1.52:1 1.33:1 1.96:1 1200 1000 800 600 400 200 0