Career Overlap Transition record Edition 1 · ESCO v1.2.1
Table 1Transition record

computer vision engineertodata quality specialist

A computer vision engineer already meets 37% of what the data quality specialist role asks for. The move turns on 11 required skills not yet in the profile.

From computer vision engineer
37%
Overlap1
To data quality specialist
12 Skills carried over
11 Required, not held
66.1 Difficulty2
Career overlap Distant match

37%

Learning distance Substantial retraining

66.1/ 100

1 Share of the data quality specialist role’s weighted skill requirement already met by the computer vision engineer 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.

Why

Why this move works

A data quality specialist role treats 9 of its required skills as things a computer vision engineer already does. These are the ones it depends on most.

  • define data quality criteria
  • establish data processes
  • handle data samples
  • implement data quality processes
  • normalise data
  • perform data cleansing

What stands in the way is 11 required skills the profile does not yet cover. Table 3 groups them; Table 4 says which to take first.

Table 2

Table 2 · What you already bring

Of the 12 skills that carry over, these are the ones fewest other occupations ask for. A data quality specialist role needs them, and most people applying for one will not have them already. This is the part of a computer vision engineer background worth leading with.

Skill the target role also needs Area
  • already held handle data samples information skills
  • already held normalise data working with computers
  • already held implement data quality processes working with computers
  • already held perform data cleansing working with computers
  • already held establish data processes working with computers
  • already held data engineering information and communication technologies (icts)

All 12 carried skills, including the 9 the data quality specialist role treats as required.

Table 3

Table 3 · What you would need to learn

The 28 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 skills 3 required, 1 supplementary
  • required, not held manage data required
  • required, not held manage database required
  • required, not held process data required
  • optional, not held execute ICT audits optional
02 information and communication technologies (icts) 2 required, 6 supplementary
  • required, not held information structure required
  • required, not held database required
  • optional, not held LDAP optional
  • optional, not held LINQ optional
  • optional, not held MDX optional
  • optional, not held N1QL optional
  • optional, not held SPARQL optional
  • optional, not held XQuery optional
03 communication, collaboration and creativity 2 required, 3 supplementary
  • required, not held design database scheme required
  • required, not held address problems critically required
  • optional, not held design database in the cloud optional
  • optional, not held build business relationships optional
  • optional, not held train employees optional
04 working with computers 2 required, 1 supplementary
  • required, not held utilise regular expressions required
  • required, not held use data processing techniques required
  • optional, not held perform data analysis optional
05 management skills 1 required, 2 supplementary
  • required, not held manage standards for data exchange required
  • optional, not held manage schedule of tasks optional
  • optional, not held perform project management optional
06 arts and humanities 1 required, 1 supplementary
  • required, not held data ethics required
  • optional, not held visual presentation techniques optional

2 further areas in the appendix

Table 4

Table 4 · Where to start

The 3 entries a data quality specialist 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 12 skills that carry over
Skill Type
  • already held define data quality criteria skill
  • already held establish data processes skill
  • already held handle data samples skill
  • already held implement data quality processes skill
  • already held normalise data skill
  • already held perform data cleansing skill
  • already held query languages knowledge
  • already held report analysis results skill
  • already held resource description framework query language knowledge
  • already held data engineering knowledge
  • already held execute analytical mathematical calculations skill
  • already held statistics knowledge
The 2 learning areas not shown above
Skill to acquire Tier
07 business, administration and law 2 supplementary
  • optional, not held data quality assessment optional
  • optional, not held business processes optional
08 health and welfare 1 supplementary
  • optional, not held healthcare analytics optional
17 supplementary skills, helpful but not required
Skill to acquire Tier
  • optional, not held LDAP optional
  • optional, not held LINQ optional
  • optional, not held MDX optional
  • optional, not held N1QL optional
  • optional, not held SPARQL optional
  • optional, not held XQuery optional
  • optional, not held data quality assessment optional
  • optional, not held design database in the cloud optional
  • optional, not held execute ICT audits optional
  • optional, not held healthcare analytics optional
  • optional, not held visual presentation techniques optional
  • optional, not held build business relationships optional
  • optional, not held business processes optional
  • optional, not held manage schedule of tasks optional
  • optional, not held perform data analysis optional
  • optional, not held perform project management optional
  • optional, not held train employees optional
40 held skills the data quality specialist role does not ask for
Skill Type
  • not needed by the target role Python (computer programming) knowledge
  • not needed by the target role apply statistical analysis techniques skill
  • not needed by the target role cognitive computing knowledge
  • not needed by the target role computer graphics knowledge
  • not needed by the target role computer programming knowledge
  • not needed by the target role computer simulation knowledge
  • not needed by the target role conduct literature research skill
  • not needed by the target role conduct qualitative research skill
  • not needed by the target role conduct quantitative research skill
  • not needed by the target role conduct scholarly research skill
  • not needed by the target role create data models skill
  • not needed by the target role data science knowledge
  • not needed by the target role debug software skill
  • not needed by the target role deep learning knowledge
  • not needed by the target role define technical requirements skill
  • not needed by the target role deliver visual presentation of data skill
  • not needed by the target role design user interface skill
  • not needed by the target role develop computer vision system skill
  • not needed by the target role develop data processing applications skill
  • not needed by the target role develop software prototype skill
  • not needed by the target role digital image processing knowledge
  • not needed by the target role digital systems knowledge
  • not needed by the target role digital twin technology knowledge
  • not needed by the target role image formation knowledge
  • not needed by the target role image recognition knowledge
  • not needed by the target role integrated development environment software knowledge
  • not needed by the target role interpret current data skill
  • not needed by the target role machine learning knowledge
  • not needed by the target role manage data collection systems skill
  • not needed by the target role mathematical modelling knowledge
  • not needed by the target role perform data mining skill
  • not needed by the target role perform dimensionality reduction skill
  • not needed by the target role principles of artificial intelligence knowledge
  • not needed by the target role quantum computing knowledge
  • not needed by the target role scientific computing knowledge
  • not needed by the target role signal processing knowledge
  • not needed by the target role state estimation knowledge
  • not needed by the target role use markup languages skill
  • not needed by the target role use software libraries skill
  • not needed by the target role utilise computer-aided software engineering tools skill
13 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 information structure required
  • required, not held data ethics required
  • required, not held database required
  • optional, not held LDAP optional
  • optional, not held LINQ optional
  • optional, not held MDX optional
  • optional, not held N1QL optional
  • optional, not held SPARQL optional
  • optional, not held XQuery optional
  • optional, not held data quality assessment optional
  • optional, not held healthcare analytics optional
  • optional, not held visual presentation techniques optional
  • optional, not held business processes optional
Index

Other moves recorded from computer vision engineer

Full index of moves from computer vision engineer

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.