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Rank
Skill
Skill gap of workers
transitioning into
this job cluster
(0 is full gap,
1 is no gap)
1
Data Science
0.19
2
Data Storage Technologies
0.41
3
Artificial Intelligence
0.10
4
Development Tools
0.73
5
Computer Networking
0.78
6
Management Consulting
0.85
7
Scientific Computing
0.41
8
Product Marketing
1.00
9
Natural Language Processing
0.11
10
Digital Marketing
1.00
11
Advertising
1.00
12
Cloud Computing
0.27
13
Customer Experience
1.00
14
Signal Processing
0.15
15
Information Management
0.93
16
Software Development Life Cycle (SDLC)
1.00
Note
The gap measure has been capped at 1.00.
Source
LinkedIn Economic Graph.
A. Opportunities within professional cluster
B. Typical skills gaps across successful job transitions
The Future of Jobs
38
Data and AI jobs of tomorrow, typical learning agenda and time to achieve mastery in key skills
F I G U R E 3 0
Rank
Skill
1
Data Analysis
2
Computer Programming
3
General Statistics
4
Leadership And Management
5
Regression
6
Machine Learning
7
Big Data
8
Python Programming
Rank
Skill
Expected
mastery score
(0 to 6, best)
Typical
mastery gap
Average
days to
master skill
1
Statistical Programming
5.50
54%
72
2
Communication
4.36
34%
80
3
Leadership and Management
3.61
66%
39
4
Data Management
3.61
45%
84
5
Marketing
3.57
55%
43
6
Finance
3.56
46%
67
7
Sales
3.43
84%
13
8
Computer Programming
3.43
41%
76
9
Business Analysis
3.24
65%
34
10
Machine Learning
3.06
54%
86
Source
Coursera.
Note
Mastery score is the score attained by those in the top 80%
on an assessment for that skill. Mastery gap is measured as
a percentage representing the score among those looking to
A. Typical learning agenda
B. Top 10 skills by required level of mastery and time to achieve that mastery
transition to the occupation as a share of the score among
those already in the occupation.
According to data from the Future of Jobs Survey,
formal upskilling appears to be more closely
focused on technology use and design skills, while
emotional intelligence skills are less frequently
targeted in that formal reskilling provision. Data from
Coursera showing the focus areas of workforce
recovery programmes and employer-led reskilling
and upskilling activities confirms that finding. In-
focus courses are primarily those in technical skills
alongside a cohort of managerial skills in strategy
and leadership.
On average, respondents to the Future of Jobs
Survey estimate that around 40% of workers will
require reskilling of six months or less. That figure is
higher for workers in the Consumer industry and in
the Health and Healthcare industry, where employers
are likely to expect to lean on short-cycle reskilling.
The share of workers who can be reskilled within
six months is lower in the Financial Services and
the Energy sectors, where employers expect that
workers will need more time-intensive reskilling.
These patterns are explored more deeply in the
Industry Profiles in Part 2.
According to Future of Jobs Survey data, employers
expect to lean primarily on internal capacity to
deliver training: 39% of training will be delivered by
an internal department. However, that training will
be supplemented by online learning platforms (16%
of training) and by external consultants (11% of
training). The trend towards the use of digital online
reskilling has accelerated during the restrictions on
in-person learning since the onset of the COVID-19
pandemic. New data from the online learning
platform Coursera for April, May and June of 2020
(quarter 2) signals a substantial expansion in the use
of online learning. In fact, there has been a four-fold
increase in the numbers of individuals seeking out
opportunities for learning online through their own
initiative, a five-fold increase in employer provision
of online learning opportunities to their workers and
an even more extensive nine-fold enrolment increase
for learners accessing online learning through
government programmes.
Through focused efforts, individuals could acquire
one of Coursera’s top 10 mastery skills in emerging
professions across People and Culture, Content
Writing, Sales and Marketing in one to two months.
Learners could expand their skills in Product
Development and Data and AI in two to three
months; and if they wish to fully re-pivot to Cloud
and Engineering, learners could make headway
into that key skill set through a 4-5 month learning
programme.
38
Such figures suggest that although
learning a new skill set is increasingly accessible
through new digital technologies, to consolidate
new learning individuals will need access to the time
and funding to pursue such new career trajectories.
LinkedIn data presented in section 2.2 indicates that
although many individuals can move into emerging
roles with low or mid skills similarity, a low-fit initial
transition will still require eventual upskilling and
reskilling to ensure long term productivity.
The Future of Jobs
39
Distribution of course enrolment and growth of interest,
by course specialism, employment status and year
F I G U R E 3 1
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