Table 1Transition record

predictive maintenance experttocomputer vision engineer

A predictive maintenance expert already meets 15% of what the computer vision engineer role asks for. The move turns on 26 required skills not yet in the profile.

From predictive maintenance expert

15%

Overlap1

To computer vision engineer

6 Skills carried over

26 Required, not held

86.6 Difficulty2

adjacent 0–30

moderate 30–55

substantial 55–75

career change 75–100

this move, 86.6

This move: 86.6 of 100 · career change

1 Share of the computer vision engineer role’s weighted skill requirement already met by the predictive maintenance expert profile. Required skills count in full, supplementary skills at 0.35. Directional: the figure for the reverse move differs. 2 Combines what is missing with how specialised it is, so a gap of general skills scores easier than the same number of narrow ones.

Table 2

Table 2 · What you already bring

Of the 6 skills that carry over, these are the ones fewest other occupations ask for. A computer vision engineer role needs them, and most people applying for one will not have them already. This is the part of a predictive maintenance expert background worth leading with.

Skill the target role also needs Area

already held develop data processing applications working with computers
already held deliver visual presentation of data communication, collaboration and creativity
already held computer simulation information and communication technologies (icts)
already held computer programming information and communication technologies (icts)
already held apply statistical analysis techniques information skills
already held statistics natural sciences, mathematics and statistics

All 6 carried skills, including the 6 the computer vision engineer role treats as required.

Table 3

Table 3 · What you would need to learn

The 46 missing skills fall into 8 areas of the ESCO skill hierarchy, numbered below in the order worth working in: the areas carrying the most required skills come first, and inside each one the required skills sit above the supplementary ones.

Skill to acquire Tier

01 information and communication technologies (icts) 9 required, 7 supplementary

required, not held Python (computer programming) required
required, not held digital twin technology required
required, not held integrated development environment software required
required, not held principles of artificial intelligence required
required, not held data engineering required
required, not held data science required
required, not held image recognition required
required, not held machine learning required
required, not held scientific computing required

optional, not held cognitive computing optional
optional, not held quantum computing optional
optional, not held query languages optional
optional, not held resource description framework query language optional
optional, not held computer graphics optional
optional, not held deep learning optional
optional, not held digital systems optional

02 working with computers 9 required, 3 supplementary

required, not held develop software prototype required
required, not held establish data processes required
required, not held normalise data required
required, not held use software libraries required
required, not held utilise computer-aided software engineering tools required
required, not held develop computer vision system required
required, not held implement data quality processes required
required, not held perform data cleansing required
required, not held perform dimensionality reduction required

optional, not held debug software optional
optional, not held perform data mining optional
optional, not held use markup languages optional

03 information skills 6 required, 4 supplementary

required, not held manage data collection systems required
required, not held conduct literature research required
required, not held execute analytical mathematical calculations required
required, not held handle data samples required
required, not held interpret current data required
required, not held report analysis results required

optional, not held create data models optional
optional, not held conduct qualitative research optional
optional, not held conduct quantitative research optional
optional, not held conduct scholarly research optional

04 arts and humanities 1 required, 1 supplementary

required, not held digital image processing required

optional, not held image formation optional

05 management skills 1 required, 1 supplementary

required, not held define technical requirements required

optional, not held define data quality criteria optional

06 engineering, manufacturing and construction 2 supplementary

optional, not held signal processing optional
optional, not held state estimation optional

2 further areas in the appendix

Table 4

Table 4 · Where to start

The 3 entries a computer vision engineer role is least likely to hire without. The ordering is computed from the skill data, not from what pays.

Each entry opens a course search for that skill. Career Overlap earns nothing from these links.

Appendix

Appendix · The rest of the record

All 6 skills that carry over

Skill Type

already held apply statistical analysis techniques skill
already held computer programming knowledge
already held computer simulation knowledge
already held deliver visual presentation of data skill
already held develop data processing applications skill
already held statistics knowledge

The 2 learning areas not shown above

Skill to acquire Tier

07 communication, collaboration and creativity 1 supplementary

optional, not held design user interface optional

08 natural sciences, mathematics and statistics 1 supplementary

optional, not held mathematical modelling optional

20 supplementary skills, helpful but not required

Skill to acquire Tier

optional, not held cognitive computing optional
optional, not held create data models optional
optional, not held debug software optional
optional, not held define data quality criteria optional
optional, not held design user interface optional
optional, not held perform data mining optional
optional, not held quantum computing optional
optional, not held query languages optional
optional, not held resource description framework query language optional
optional, not held signal processing optional
optional, not held use markup languages optional
optional, not held computer graphics optional
optional, not held conduct qualitative research optional
optional, not held conduct quantitative research optional
optional, not held conduct scholarly research optional
optional, not held deep learning optional
optional, not held digital systems optional
optional, not held image formation optional
optional, not held mathematical modelling optional
optional, not held state estimation optional

19 held skills the computer vision engineer role does not ask for

Skill Type

not needed by the target role ICT networking hardware knowledge
not needed by the target role advise on equipment maintenance skill
not needed by the target role analyse big data skill
not needed by the target role apply information security policies skill
not needed by the target role automotive diagnostic equipment knowledge
not needed by the target role automotive engineering skill
not needed by the target role design sensors skill
not needed by the target role electrical engineering knowledge
not needed by the target role electricity knowledge
not needed by the target role electronics knowledge
not needed by the target role ensure equipment maintenance skill
not needed by the target role gather data skill
not needed by the target role manage data skill
not needed by the target role mathematics knowledge
not needed by the target role model sensor skill
not needed by the target role perform data analysis skill
not needed by the target role predictive maintenance knowledge
not needed by the target role test sensors skill
not needed by the target role use automotive diagnostic equipment skill

21 gaps that are knowledge rather than practice

Knowledge gaps usually close through study. Practical skill gaps usually need something you can point at.

Skill to acquire Tier

required, not held Python (computer programming) required
required, not held digital twin technology required
required, not held integrated development environment software required
required, not held principles of artificial intelligence required
required, not held data engineering required
required, not held data science required
required, not held digital image processing required
required, not held image recognition required
required, not held machine learning required
required, not held scientific computing required
optional, not held cognitive computing optional
optional, not held quantum computing optional
optional, not held query languages optional
optional, not held resource description framework query language optional
optional, not held signal processing optional
optional, not held computer graphics optional
optional, not held deep learning optional
optional, not held digital systems optional
optional, not held image formation optional
optional, not held mathematical modelling optional
optional, not held state estimation optional

Index

Other moves recorded from predictive maintenance expert

Full index of moves from predictive maintenance expert

Note

How this record was compiled

Both occupations are taken from ESCO, which lists the skills and knowledge each occupation is expected to have and marks every one required or optional. Nothing here is a prediction about hiring, and nothing here knows that a particular employer wants a particular certificate. Treat Table 3 as a starting point for your own research rather than a syllabus. The full method states what these figures can and cannot tell you.