RecordMove

Monitoring and evaluation officer to computer vision engineer

A monitoring and evaluation officer already meets 16% of what the computer vision engineer role asks for. The move turns on 27 required skills not yet in the profile.

Fig. 1 · Skill transfer ESCO v1.2.1 · directional

From monitoring and evaluation officer

Distant match

To computer vision engineer

8 You already bring

27 Still to learn

52 Skills in the target role2

Learning distance A rebuild

86.7/ 100

adjacentmoderatesubstantialcareer change

1 How much of what a computer vision engineer is expected to do is already part of a monitoring and evaluation officer’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

Why this move works

A computer vision engineer role treats 5 of its required skills as things a monitoring and evaluation officer already does. You would walk in with these on day one.

apply statistical analysis techniques
implement data quality processes
manage data collection systems
perform data cleansing
report analysis results

What stands in the way is 27 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 8 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 monitoring and evaluation officer background worth leading with.

Skill the target role also needs Area

already held implement data quality processes working with computers
already held perform data cleansing working with computers
already held create data models information skills
already held manage data collection systems information skills
already held report analysis results information skills
already held conduct qualitative research information skills

All 8 carried skills, including the 5 the computer vision engineer role treats as required.

Table 3

Table 3 · What you may need to learn

The 44 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.

Skill to pick up Tier

01 information and communication technologies (icts) 11 required, 7 supplementary

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 data engineering required
still to learn data science required
still to learn image recognition 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 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 8 required, 3 supplementary

still to learn develop data processing applications required
still to learn develop software prototype required
still to learn establish data processes required
still to learn normalise data 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 perform data mining optional
optional, not held use markup languages optional

03 information skills 4 required, 1 supplementary

still to learn conduct literature research required
still to learn execute analytical mathematical calculations required
still to learn handle data samples required
still to learn interpret current data required

optional, not held conduct scholarly research optional

04 arts and humanities 1 required, 1 supplementary

still to learn digital image processing required

optional, not held image formation optional

05 communication, collaboration and creativity 1 required, 1 supplementary

still to learn deliver visual presentation of data required

optional, not held design user interface optional

06 management skills 1 required, 1 supplementary

still to learn define technical requirements required

optional, not held define data quality criteria 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 8 skills that carry over

Skill Type

already held apply statistical analysis techniques skill
already held implement data quality processes skill
already held manage data collection systems skill
already held perform data cleansing skill
already held report analysis results skill
already held conduct qualitative research skill
already held conduct quantitative research skill
already held create data models skill

The 2 learning areas not shown above

Skill to pick up Tier

07 natural sciences, mathematics and statistics 1 required, 1 supplementary

still to learn statistics required

optional, not held mathematical modelling optional

08 engineering, manufacturing and construction 2 supplementary

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

17 supplementary skills, helpful but not required

Skill to pick up Tier

optional, not held cognitive computing 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 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

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

Skill Type

not needed by the target role adapt evaluation methodology skill
not needed by the target role apply organisational techniques skill
not needed by the target role commission evaluation skill
not needed by the target role communicate with stakeholders skill
not needed by the target role conduct training on monitoring and evaluation frameworks skill
not needed by the target role create data sets skill
not needed by the target role data protection knowledge
not needed by the target role define evaluation objectives and scope skill
not needed by the target role design questionnaires skill
not needed by the target role develop communications strategies skill
not needed by the target role development economics knowledge
not needed by the target role engage with stakeholders skill
not needed by the target role ethics knowledge
not needed by the target role evaluation theory knowledge
not needed by the target role formulate findings skill
not needed by the target role gather data for forensic purposes skill
not needed by the target role information confidentiality knowledge
not needed by the target role international development knowledge
not needed by the target role interview people skill
not needed by the target role maintain data entry requirements skill
not needed by the target role manage data skill
not needed by the target role manage project metrics skill
not needed by the target role manage quantitative data skill
not needed by the target role manage resources skill
not needed by the target role monitor recommendation follow-up skill
not needed by the target role observe confidentiality skill
not needed by the target role perform data analysis skill
not needed by the target role plan evaluation skill
not needed by the target role policy analysis knowledge
not needed by the target role process qualitative information skill
not needed by the target role promote evaluation capacity development skill
not needed by the target role reconstruct program theory skill
not needed by the target role respect data protection principles skill
not needed by the target role results-based management knowledge
not needed by the target role scientific research methodology knowledge
not needed by the target role survey techniques knowledge
not needed by the target role sustainable development goals knowledge
not needed by the target role systems thinking knowledge
not needed by the target role types of evaluation knowledge
not needed by the target role use databases skill

1 further entry not listed here

24 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 pick up Tier

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 data engineering required
still to learn data science required
still to learn digital image processing required
still to learn image recognition required
still to learn machine learning required
still to learn scientific computing required
still to learn statistics 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 monitoring and evaluation officer

Full index of moves from monitoring and evaluation officer

FAQ

Common questions about this move

Can a monitoring and evaluation officer become a computer vision engineer?

Yes, and it is a career change move. A monitoring and evaluation officer already covers 16% of what a computer vision engineer is expected to do: 8 skills carry over, 5 of which the computer vision engineer role treats as required.

What skills does a monitoring and evaluation officer need to become a computer vision engineer?

27 required skills are missing, plus 17 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 monitoring and evaluation officer to computer vision engineer?

Its learning distance is 86.7 out of 100, which is the career change band. That accounts for both how much is missing and how specialised those skills are.

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.