Data analyst to computer 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.
66/ 100
1 How much of what a computer vision engineer is expected to do is already part of a data analyst’s work. Directional: the figure for the reverse move differs, because moving into a speciality is not the same problem as moving out of one. 2 Every skill the computer vision engineer role is recorded as needing, required and optional together. What these numbers mean.
Why this move works
A computer vision engineer role treats 15 of its required skills as things a data analyst already does. You would walk in with these on day one.
- apply statistical analysis techniques
- data engineering
- data science
- deliver visual presentation of data
- establish data processes
- execute analytical mathematical calculations
What stands in the way is 17 required skills the profile does not yet cover. Table 3 groups them; Table 4 says which to take first.
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.
- 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 · What you may need to learn
The 32 missing skills fall into 8 areas of the ESCO skill hierarchy, numbered in the order worth working in. Areas carrying the most required skills come first, and inside each one the required skills sit above the optional ones. Nothing here is a verdict on you: it is a list of what this particular job asks for that your current one does not.
- still to learn Python (computer programming) required
- still to learn digital twin technology required
- still to learn integrated development environment software required
- still to learn principles of artificial intelligence required
- still to learn computer programming required
- still to learn computer simulation required
- still to learn machine learning required
- still to learn 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
- still to learn develop data processing applications required
- still to learn develop software prototype required
- still to learn use software libraries required
- still to learn utilise computer-aided software engineering tools required
- still to learn develop computer vision system required
- still to learn perform dimensionality reduction required
- optional, not held debug software optional
- optional, not held use markup languages optional
- still to learn 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
- still to learn digital image processing required
- optional, not held image formation optional
- still to learn define technical requirements required
- optional, not held signal processing optional
- optional, not held state estimation optional
2 further areas in the appendix
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.
- 01 develop data processing applications practise this
- 02 Python (computer programming) study this
- 03 develop software prototype practise this
Each entry opens a course search for that skill. Career Overlap earns nothing from these links.
Appendix · The rest of the record
All 20 skills that carry over
- 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
- optional, not held design user interface optional
- optional, not held mathematical modelling optional
15 supplementary skills, helpful but not required
- 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
- 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.
- still to learn Python (computer programming) required
- still to learn digital twin technology required
- still to learn integrated development environment software required
- still to learn principles of artificial intelligence required
- still to learn computer programming required
- still to learn computer simulation required
- still to learn digital image processing required
- still to learn machine learning required
- still to learn 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
Other moves recorded from data analyst
- data quality specialist 67% covered · moderate
- data entry clerk 63% covered · moderate
- chief data officer 56% covered · moderate
- ICT information and knowledge manager 50% covered · substantial
- data entry supervisor 49% covered · substantial
- data engineer 47% covered · substantial
- data scientist 47% covered · substantial
- big data archive librarian 32% covered · career change
Common questions about this move
Can a data analyst become a computer vision engineer?
Yes, and it is a substantial move. A data analyst already covers 43% of what a computer vision engineer is expected to do: 20 skills carry over, 15 of which the computer vision engineer role treats as required.
What skills does a data analyst need to become a computer vision engineer?
17 required skills are missing, plus 15 optional ones. They fall into 8 areas of the ESCO skill hierarchy, led by information and communication technologies (icts). The single most important is develop data processing applications.
How hard is the move from data analyst to computer vision engineer?
Its learning distance is 66 out of 100, which is the substantial band. That accounts for both how much is missing and how specialised those skills are.
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.