Table 1Transition record

data analysttocomputer vision engineer

A data analyst already meets 43% of what the computer vision engineer role asks for. The move turns on 17 required skills not yet in the profile.

From data analyst

43%

Overlap1

To computer vision engineer

20 Skills carried over

17 Required, not held

66 Difficulty2

adjacent 0–30

moderate 30–55

substantial 55–75

career change 75–100

this move, 66

This move: 66 of 100 · substantial

1 Share of the computer vision engineer role’s weighted skill requirement already met by the data analyst 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 20 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 data analyst 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 image recognition information and communication technologies (icts)
already held perform data cleansing working with computers
already held establish data processes working with computers

All 20 carried skills, including the 15 the computer vision engineer role treats as required.

Table 3

Table 3 · What you would need to learn

The 32 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) 8 required, 5 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 computer programming required
required, not held computer simulation 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 computer graphics optional
optional, not held deep learning optional
optional, not held digital systems optional

02 working with computers 6 required, 2 supplementary

required, not held develop data processing applications required
required, not held develop software prototype 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 perform dimensionality reduction required

optional, not held debug software optional
optional, not held use markup languages optional

03 information skills 1 required, 3 supplementary

required, not held conduct literature research required

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

required, not held define technical requirements required

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 20 skills that carry over

Skill Type

already held apply statistical analysis techniques skill
already held data engineering knowledge
already held data science knowledge
already held deliver visual presentation of data skill
already held establish data processes skill
already held execute analytical mathematical calculations skill
already held handle data samples skill
already held image recognition knowledge
already held implement data quality processes skill
already held interpret current data skill
already held manage data collection systems skill
already held normalise data skill
already held perform data cleansing skill
already held report analysis results skill
already held statistics knowledge
already held create data models skill
already held define data quality criteria skill
already held perform data mining skill
already held query languages knowledge
already held resource description framework query language 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

15 supplementary skills, helpful but not required

Skill to acquire Tier

optional, not held cognitive computing optional
optional, not held debug software optional
optional, not held design user interface optional
optional, not held quantum computing 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

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

Skill Type

not needed by the target role Hadoop knowledge
not needed by the target role LDAP knowledge
not needed by the target role LINQ knowledge
not needed by the target role MDX knowledge
not needed by the target role N1QL knowledge
not needed by the target role SPARQL knowledge
not needed by the target role XQuery knowledge
not needed by the target role analyse big data skill
not needed by the target role business analytics knowledge
not needed by the target role business intelligence knowledge
not needed by the target role cloud technologies knowledge
not needed by the target role collect ICT data skill
not needed by the target role data ethics knowledge
not needed by the target role data mining knowledge
not needed by the target role data models knowledge
not needed by the target role data quality assessment knowledge
not needed by the target role data storage knowledge
not needed by the target role data visualisation software knowledge
not needed by the target role database knowledge
not needed by the target role digital data processing skill
not needed by the target role documentation types knowledge
not needed by the target role game theory knowledge
not needed by the target role gather data for forensic purposes skill
not needed by the target role healthcare analytics knowledge
not needed by the target role information architecture knowledge
not needed by the target role information categorisation knowledge
not needed by the target role information confidentiality knowledge
not needed by the target role information extraction knowledge
not needed by the target role information structure knowledge
not needed by the target role integrate ICT data skill
not needed by the target role make data-driven decisions skill
not needed by the target role manage cloud data and storage skill
not needed by the target role manage data skill
not needed by the target role manage quantitative data skill
not needed by the target role marketing analytics knowledge
not needed by the target role multidisciplinary research knowledge
not needed by the target role online analytical processing knowledge
not needed by the target role research design knowledge
not needed by the target role social network analysis knowledge
not needed by the target role statistical modeling techniques knowledge

7 further entries not listed here

18 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 computer programming required
required, not held computer simulation required
required, not held digital image processing 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 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 data analyst

Full index of moves from data analyst

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.