Data scientist to data quality specialist
A data scientist already meets 66% of what the data quality specialist role asks for. The move turns on 7 required skills not yet in the profile.
39.3/ 100
1 How much of what a data quality specialist is expected to do is already part of a data scientist’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 data quality specialist role is recorded as needing, required and optional together. What these numbers mean.
Why this move works
A data quality specialist role treats 13 of its required skills as things a data scientist already does. You would walk in with these on day one.
- data ethics
- define data quality criteria
- design database scheme
- establish data processes
- handle data samples
- implement data quality processes
What stands in the way is 7 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 27 skills that carry over, these are the ones fewest other occupations ask for. A data quality specialist role needs them, and most people applying for one will not have them already. This is the part of a data scientist background worth leading with.
- 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 13 the data quality specialist role treats as required.
Table 3 · What you may need to learn
The 13 missing skills fall into 6 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 manage database required
- still to learn process data required
- optional, not held execute ICT audits optional
- still to learn information structure required
- still to learn database required
- still to learn address problems critically required
- optional, not held build business relationships optional
- optional, not held train employees optional
- still to learn manage standards for data exchange required
- optional, not held manage schedule of tasks optional
- still to learn utilise regular expressions required
- optional, not held perform data analysis optional
- optional, not held business processes optional
Table 4 · Where to start
The 3 entries a data quality specialist role is least likely to hire without. The ordering is computed from the skill data, not from what pays.
- 01 utilise regular expressions practise this
- 02 information structure study this
- 03 manage standards for data exchange 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 27 skills that carry over
- already held data ethics knowledge
- already held define data quality criteria skill
- already held design database scheme skill
- already held establish data processes skill
- already held handle data samples skill
- already held implement data quality processes skill
- already held manage data skill
- already held normalise data skill
- already held perform data cleansing skill
- already held query languages knowledge
- already held report analysis results skill
- already held resource description framework query language knowledge
- already held use data processing techniques skill
- 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 engineering knowledge
- already held data quality assessment knowledge
- already held design database in the cloud skill
- already held execute analytical mathematical calculations skill
- already held healthcare analytics knowledge
- already held perform project management skill
- already held statistics knowledge
- already held visual presentation techniques knowledge
6 supplementary skills, helpful but not required
- optional, not held execute ICT audits optional
- optional, not held build business relationships optional
- optional, not held business processes optional
- optional, not held manage schedule of tasks optional
- optional, not held perform data analysis optional
- optional, not held train employees optional
70 held skills the data quality specialist role does not ask for
- not needed by the target role Hadoop knowledge
- not needed by the target role apply blended learning skill
- not needed by the target role apply for research funding skill
- not needed by the target role apply research ethics and scientific integrity principles in research activities skill
- not needed by the target role build recommender systems 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 collect ICT data skill
- not needed by the target role communicate with a non-scientific audience skill
- not needed by the target role computational biology knowledge
- not needed by the target role computer simulation knowledge
- not needed by the target role conduct research across disciplines skill
- not needed by the target role create data models skill
- 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 science knowledge
- not needed by the target role data visualisation software knowledge
- not needed by the target role deliver visual presentation of data skill
- not needed by the target role demonstrate disciplinary expertise skill
- not needed by the target role develop data processing applications skill
- not needed by the target role develop professional network with researchers and scientists skill
- not needed by the target role digital curation knowledge
- not needed by the target role disseminate results to the scientific community skill
- not needed by the target role draft scientific or academic papers and technical documentation skill
- not needed by the target role empirical analysis knowledge
- not needed by the target role evaluate research activities skill
- not needed by the target role image recognition knowledge
- not needed by the target role increase the impact of science on policy and society skill
- not needed by the target role information categorisation knowledge
- not needed by the target role information extraction knowledge
- not needed by the target role integrate ICT data skill
- not needed by the target role integrate gender dimension in research skill
- not needed by the target role interact professionally in research and professional environments skill
- not needed by the target role interpret current data skill
- not needed by the target role make data-driven decisions skill
- not needed by the target role manage ICT data architecture skill
- not needed by the target role manage ICT data classification skill
- not needed by the target role manage data collection systems skill
- not needed by the target role manage findable accessible interoperable and reusable data skill
- not needed by the target role manage intellectual property rights skill
30 further entries not listed here
3 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 information structure required
- still to learn database required
- optional, not held business processes optional
Other moves recorded from data scientist
- data analyst 80% covered · moderate
- demographer 72% covered · moderate
- biometrician 69% covered · moderate
- religion scientific researcher 69% covered · moderate
- statistician 68% covered · moderate
- astronomer 67% covered · moderate
- seismologist 66% covered · moderate
- philosopher 65% covered · moderate
Common questions about this move
Can a data scientist become a data quality specialist?
Yes, and it is a moderate move. A data scientist already covers 66% of what a data quality specialist is expected to do: 27 skills carry over, 13 of which the data quality specialist role treats as required.
What skills does a data scientist need to become a data quality specialist?
7 required skills are missing, plus 6 optional ones. They fall into 6 areas of the ESCO skill hierarchy, led by information skills. The single most important is utilise regular expressions.
How hard is the move from data scientist to data quality specialist?
Its learning distance is 39.3 out of 100, which is the moderate 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.