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

data quality specialisttodata scientist

A data quality specialist already meets 27% of what the data scientist role asks for. The move turns on 47 required skills not yet in the profile.

From data quality specialist
27%
Overlap1
To data scientist
27 Skills carried over
47 Required, not held
83.1 Difficulty2
Career overlap Distant match

27%

Learning distance A rebuild

83.1/ 100

1 Share of the data scientist role’s weighted skill requirement already met by the data quality specialist 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 scientist role treats 16 of its required skills as things a data quality specialist already does. These are the ones it depends on most.

  • data engineering
  • data ethics
  • design database scheme
  • establish data processes
  • execute analytical mathematical calculations
  • handle data samples

What stands in the way is 47 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 27 skills that carry over, these are the ones fewest other occupations ask for. A data scientist role needs them, and most people applying for one will not have them already. This is the part of a data quality specialist background worth leading with.

Skill the target role also needs Area
  • already held handle data samples information skills
  • already held data ethics arts and humanities
  • already held normalise data working with computers
  • already held healthcare analytics health and welfare
  • already held implement data quality processes working with computers
  • already held perform data cleansing working with computers

All 27 carried skills, including the 16 the data scientist role treats as required.

Table 3

Table 3 · What you would need to learn

The 70 missing skills fall into 10 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 communication, collaboration and creativity 15 required, 3 supplementary
  • required, not held manage intellectual property rights required
  • required, not held communicate with a non-scientific audience required
  • required, not held deliver visual presentation of data required
  • required, not held develop professional network with researchers and scientists required
  • required, not held disseminate results to the scientific community required
  • required, not held draft scientific or academic papers and technical documentation required
  • required, not held evaluate research activities required
  • required, not held increase the impact of science on policy and society required
  • required, not held interact professionally in research and professional environments required
  • required, not held mentor individuals required
  • required, not held promote the transfer of knowledge required
  • required, not held publish academic research required
  • required, not held speak different languages required
  • required, not held think abstractly required
  • required, not held write scientific publications required
  • optional, not held manage ICT data architecture optional
  • optional, not held apply blended learning optional
  • optional, not held teach in academic or vocational contexts optional
02 information skills 14 required, 2 supplementary
  • required, not held manage data collection systems required
  • required, not held apply for research funding required
  • required, not held apply research ethics and scientific integrity principles in research activities required
  • required, not held collect ICT data required
  • required, not held conduct research across disciplines required
  • required, not held demonstrate disciplinary expertise required
  • required, not held integrate gender dimension in research required
  • required, not held interpret current data required
  • required, not held manage findable accessible interoperable and reusable data required
  • required, not held manage research data required
  • required, not held perform scientific research required
  • required, not held promote open innovation in research required
  • required, not held promote the participation of citizens in scientific and research activities required
  • required, not held synthesise information required
  • optional, not held create data models optional
  • optional, not held make data-driven decisions optional
03 information and communication technologies (icts) 6 required, 5 supplementary
  • required, not held data mining required
  • required, not held data models required
  • required, not held information extraction required
  • required, not held online analytical processing required
  • required, not held data science required
  • required, not held data visualisation software required
  • optional, not held Hadoop optional
  • optional, not held unstructured data optional
  • optional, not held computer simulation optional
  • optional, not held image recognition optional
  • optional, not held scientific computing optional
04 working with computers 5 required, 4 supplementary
  • required, not held build recommender systems required
  • required, not held develop data processing applications required
  • required, not held operate open source software required
  • required, not held manage open publications required
  • required, not held use databases required
  • optional, not held integrate ICT data optional
  • optional, not held manage ICT data classification optional
  • optional, not held perform data mining optional
  • optional, not held use spreadsheets software optional
05 generic programmes and qualifications 2 required, 2 supplementary
  • required, not held empirical analysis required
  • required, not held scientific literature required
  • optional, not held multidisciplinary research optional
  • optional, not held research design optional
06 natural sciences, mathematics and statistics 2 required, 2 supplementary
  • required, not held statistical modeling techniques required
  • required, not held mathematical modelling required
  • optional, not held business analytics optional
  • optional, not held computational biology optional

4 further areas in the appendix

Table 4

Table 4 · Where to start

The 3 entries a data scientist 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 27 skills that carry over
Skill Type
  • already held data engineering knowledge
  • already held data ethics knowledge
  • already held design database scheme skill
  • already held establish data processes skill
  • already held execute analytical mathematical calculations 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 perform project management skill
  • already held query languages knowledge
  • already held report analysis results skill
  • already held resource description framework query language knowledge
  • already held statistics knowledge
  • already held use data processing techniques skill
  • already held visual presentation techniques knowledge
  • already held LDAP knowledge
  • already held LINQ knowledge
  • already held MDX knowledge
  • already held N1QL knowledge
  • already held SPARQL knowledge
  • already held XQuery knowledge
  • already held data quality assessment knowledge
  • already held define data quality criteria skill
  • already held design database in the cloud skill
  • already held healthcare analytics knowledge
  • already held manage data skill
The 4 learning areas not shown above
Skill to acquire Tier
07 social sciences, journalism and information 2 required, 2 supplementary
  • required, not held information categorisation required
  • required, not held quantitative analysis required
  • optional, not held digital curation optional
  • optional, not held social network analysis optional
08 management skills 1 required
  • required, not held manage personal professional development required
09 business, administration and law 2 supplementary
  • optional, not held business intelligence optional
  • optional, not held marketing analytics optional
10 engineering, manufacturing and construction 1 supplementary
  • optional, not held state estimation optional
23 supplementary skills, helpful but not required
Skill to acquire Tier
  • optional, not held digital curation optional
  • optional, not held Hadoop optional
  • optional, not held business analytics optional
  • optional, not held computational biology optional
  • optional, not held create data models optional
  • optional, not held integrate ICT data optional
  • optional, not held manage ICT data architecture optional
  • optional, not held manage ICT data classification optional
  • optional, not held perform data mining optional
  • optional, not held unstructured data optional
  • optional, not held apply blended learning optional
  • optional, not held business intelligence optional
  • optional, not held computer simulation optional
  • optional, not held image recognition optional
  • optional, not held make data-driven decisions optional
  • optional, not held marketing analytics optional
  • optional, not held multidisciplinary research optional
  • optional, not held research design optional
  • optional, not held scientific computing optional
  • optional, not held social network analysis optional
  • optional, not held state estimation optional
  • optional, not held teach in academic or vocational contexts optional
  • optional, not held use spreadsheets software optional
13 held skills the data scientist role does not ask for
Skill Type
  • not needed by the target role address problems critically skill
  • not needed by the target role build business relationships skill
  • not needed by the target role business processes knowledge
  • not needed by the target role database knowledge
  • not needed by the target role execute ICT audits skill
  • not needed by the target role information structure knowledge
  • not needed by the target role manage database skill
  • not needed by the target role manage schedule of tasks skill
  • not needed by the target role manage standards for data exchange skill
  • not needed by the target role perform data analysis skill
  • not needed by the target role process data skill
  • not needed by the target role train employees skill
  • not needed by the target role utilise regular expressions skill
26 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 data mining required
  • required, not held data models required
  • required, not held information categorisation required
  • required, not held information extraction required
  • required, not held online analytical processing required
  • required, not held statistical modeling techniques required
  • required, not held data science required
  • required, not held data visualisation software required
  • required, not held empirical analysis required
  • required, not held mathematical modelling required
  • required, not held quantitative analysis required
  • required, not held scientific literature required
  • optional, not held digital curation optional
  • optional, not held Hadoop optional
  • optional, not held business analytics optional
  • optional, not held computational biology optional
  • optional, not held unstructured data optional
  • optional, not held business intelligence optional
  • optional, not held computer simulation optional
  • optional, not held image recognition optional
  • optional, not held marketing analytics optional
  • optional, not held multidisciplinary research optional
  • optional, not held research design optional
  • optional, not held scientific computing optional
  • optional, not held social network analysis optional
  • optional, not held state estimation optional
Index

Other moves recorded from data quality specialist

Full index of moves from data quality specialist

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.