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

statistical assistanttopredictive maintenance expert

A statistical assistant already meets 29% of what the predictive maintenance expert role asks for. The move turns on 14 required skills not yet in the profile.

From statistical assistant
29%
Overlap1
To predictive maintenance expert
7 Skills carried over
14 Required, not held
69.6 Difficulty2
Career overlap Distant match

29%

Learning distance Substantial retraining

69.6/ 100

1 Share of the predictive maintenance expert role’s weighted skill requirement already met by the statistical assistant 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 predictive maintenance expert role treats 6 of its required skills as things a statistical assistant already does. These are the ones it depends on most.

  • analyse big data
  • apply statistical analysis techniques
  • gather data
  • mathematics
  • perform data analysis
  • statistics

What stands in the way is 14 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 7 skills that carry over, these are the ones fewest other occupations ask for. A predictive maintenance expert role needs them, and most people applying for one will not have them already. This is the part of a statistical assistant background worth leading with.

Skill the target role also needs Area
  • already held gather data information skills
  • already held deliver visual presentation of data communication, collaboration and creativity
  • already held analyse big data information skills
  • already held apply statistical analysis techniques information skills
  • already held perform data analysis working with computers
  • already held statistics natural sciences, mathematics and statistics

All 7 carried skills, including the 6 the predictive maintenance expert role treats as required.

Table 3

Table 3 · What you would need to learn

The 18 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 engineering, manufacturing and construction 4 required, 1 supplementary
  • required, not held predictive maintenance required
  • required, not held electrical engineering required
  • required, not held electricity required
  • required, not held electronics required
  • optional, not held automotive diagnostic equipment optional
02 communication, collaboration and creativity 3 required, 1 supplementary
  • required, not held design sensors required
  • required, not held model sensor required
  • required, not held advise on equipment maintenance required
  • optional, not held automotive engineering optional
03 information and communication technologies (icts) 2 required, 1 supplementary
  • required, not held ICT networking hardware required
  • required, not held computer programming required
  • optional, not held computer simulation optional
04 constructing 1 required, 1 supplementary
  • required, not held test sensors required
  • optional, not held use automotive diagnostic equipment optional
05 assisting and caring 1 required
  • required, not held apply information security policies required
06 information skills 1 required
  • required, not held manage data required

2 further areas in the appendix

Table 4

Table 4 · Where to start

The 3 entries a predictive maintenance expert 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 7 skills that carry over
Skill Type
  • already held analyse big data skill
  • already held apply statistical analysis techniques skill
  • already held gather data skill
  • already held mathematics knowledge
  • already held perform data analysis skill
  • already held statistics knowledge
  • already held deliver visual presentation of data skill
The 2 learning areas not shown above
Skill to acquire Tier
07 management skills 1 required
  • required, not held ensure equipment maintenance required
08 working with computers 1 required
  • required, not held develop data processing applications required
4 supplementary skills, helpful but not required
Skill to acquire Tier
  • optional, not held automotive diagnostic equipment optional
  • optional, not held use automotive diagnostic equipment optional
  • optional, not held automotive engineering optional
  • optional, not held computer simulation optional
31 held skills the predictive maintenance expert role does not ask for
Skill Type
  • not needed by the target role algorithms knowledge
  • not needed by the target role apply scientific methods skill
  • not needed by the target role assist scientific research skill
  • not needed by the target role carry out statistical forecasts skill
  • not needed by the target role compile statistical data for insurance purposes skill
  • not needed by the target role conduct financial surveys skill
  • not needed by the target role conduct public surveys skill
  • not needed by the target role conduct quantitative research skill
  • not needed by the target role data quality assessment knowledge
  • not needed by the target role data science knowledge
  • not needed by the target role design questionnaires skill
  • not needed by the target role develop financial statistics reports skill
  • not needed by the target role digital data processing skill
  • not needed by the target role execute analytical mathematical calculations skill
  • not needed by the target role identify statistical patterns skill
  • not needed by the target role manage database skill
  • not needed by the target role perform clerical duties skill
  • not needed by the target role perform scientific research skill
  • not needed by the target role process data skill
  • not needed by the target role produce statistical financial records skill
  • not needed by the target role quantitative analysis knowledge
  • not needed by the target role research design knowledge
  • not needed by the target role revise questionnaires skill
  • not needed by the target role scientific research methodology knowledge
  • not needed by the target role statistical analysis system software knowledge
  • not needed by the target role statistical modeling techniques knowledge
  • not needed by the target role survey techniques knowledge
  • not needed by the target role tabulate survey results skill
  • not needed by the target role use spreadsheets software skill
  • not needed by the target role write technical reports skill
  • not needed by the target role write work-related reports skill
8 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 predictive maintenance required
  • required, not held ICT networking hardware required
  • required, not held computer programming required
  • required, not held electrical engineering required
  • required, not held electricity required
  • required, not held electronics required
  • optional, not held automotive diagnostic equipment optional
  • optional, not held computer simulation optional
Index
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.