Data scientist to data analyst
A data scientist already meets 80% of what the data analyst role asks for. The move turns on 6 required skills not yet in the profile.
32.3/ 100
1 How much of what a data analyst 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 analyst role is recorded as needing, required and optional together. What these numbers mean.
Why this move works
A data analyst role treats 30 of its required skills as things a data scientist already does. You would walk in with these on day one.
- business analytics
- business intelligence
- collect ICT data
- data engineering
- data ethics
- data mining
What stands in the way is 6 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 51 skills that carry over, these are the ones fewest other occupations ask for. A data analyst 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 collect ICT data information skills
- already held Hadoop information and communication technologies (icts)
- already held handle data samples information skills
- already held data ethics arts and humanities
- already held integrate ICT data working with computers
- already held normalise data working with computers
All 51 carried skills, including the 30 the data analyst role treats as required.
Table 3 · What you may need to learn
The 16 missing skills fall into 5 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 information confidentiality required
- still to learn information structure required
- optional, not held cloud technologies optional
- optional, not held data storage optional
- optional, not held information architecture optional
- optional, not held database optional
- optional, not held web analytics optional
- still to learn analyse big data required
- still to learn apply statistical analysis techniques required
- optional, not held gather data for forensic purposes optional
- optional, not held manage cloud data and storage optional
- still to learn digital data processing required
- optional, not held manage quantitative data optional
- optional, not held store digital data and systems optional
- still to learn documentation types required
- optional, not held game theory optional
Table 4 · Where to start
The 3 entries a data analyst role is least likely to hire without. The ordering is computed from the skill data, not from what pays.
- 01 digital data processing practise this
- 02 documentation types study this
- 03 information confidentiality study this
Each entry opens a course search for that skill. Career Overlap earns nothing from these links.
Appendix · The rest of the record
All 51 skills that carry over
- already held business analytics knowledge
- already held business intelligence knowledge
- already held collect ICT data skill
- already held data engineering knowledge
- already held data ethics knowledge
- already held data mining knowledge
- already held data models knowledge
- already held data quality assessment knowledge
- already held data science knowledge
- already held data visualisation software knowledge
- already held define data quality criteria 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 information categorisation knowledge
- already held information extraction knowledge
- already held integrate ICT data skill
- already held interpret current data skill
- already held manage data skill
- already held normalise data skill
- already held perform data cleansing skill
- already held perform data mining skill
- already held query languages knowledge
- already held resource description framework query language knowledge
- already held statistics knowledge
- already held unstructured data knowledge
- already held use data processing techniques skill
- already held use databases skill
- already held visual presentation techniques knowledge
- already held Hadoop 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 create data models skill
- already held deliver visual presentation of data skill
- already held healthcare analytics knowledge
- already held image recognition knowledge
- already held make data-driven decisions skill
- already held manage data collection systems skill
- already held marketing analytics knowledge
- already held multidisciplinary research knowledge
- already held online analytical processing knowledge
- already held report analysis results skill
- already held research design knowledge
- already held social network analysis knowledge
- already held statistical modeling techniques knowledge
- already held use spreadsheets software skill
10 supplementary skills, helpful but not required
- optional, not held cloud technologies optional
- optional, not held data storage optional
- optional, not held gather data for forensic purposes optional
- optional, not held information architecture optional
- optional, not held manage cloud data and storage optional
- optional, not held database optional
- optional, not held game theory optional
- optional, not held manage quantitative data optional
- optional, not held store digital data and systems optional
- optional, not held web analytics optional
46 held skills the data analyst role does not ask for
- 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 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 demonstrate disciplinary expertise skill
- not needed by the target role design database in the cloud skill
- not needed by the target role design database scheme 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 increase the impact of science on policy and society 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 manage ICT data architecture skill
- not needed by the target role manage ICT data classification 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
- not needed by the target role manage open publications skill
- not needed by the target role manage personal professional development skill
- not needed by the target role manage research data skill
- not needed by the target role mathematical modelling knowledge
- not needed by the target role mentor individuals skill
- not needed by the target role operate open source software skill
- not needed by the target role perform project management skill
- not needed by the target role perform scientific research skill
- not needed by the target role promote open innovation in research skill
- not needed by the target role promote the participation of citizens in scientific and research activities skill
- not needed by the target role promote the transfer of knowledge skill
- not needed by the target role publish academic research skill
- not needed by the target role quantitative analysis knowledge
- not needed by the target role scientific computing knowledge
- not needed by the target role scientific literature knowledge
6 further entries not listed here
9 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 documentation types required
- still to learn information confidentiality required
- still to learn information structure required
- optional, not held cloud technologies optional
- optional, not held data storage optional
- optional, not held information architecture optional
- optional, not held database optional
- optional, not held game theory optional
- optional, not held web analytics optional
Other moves recorded from data scientist
- demographer 72% covered · moderate
- biometrician 69% covered · moderate
- religion scientific researcher 69% covered · moderate
- statistician 68% covered · moderate
- astronomer 67% covered · moderate
- data quality specialist 66% covered · moderate
- seismologist 66% covered · moderate
- philosopher 65% covered · moderate
Common questions about this move
Can a data scientist become a data analyst?
Yes, and it is a moderate move. A data scientist already covers 80% of what a data analyst is expected to do: 51 skills carry over, 30 of which the data analyst role treats as required.
What skills does a data scientist need to become a data analyst?
6 required skills are missing, plus 10 optional ones. They fall into 5 areas of the ESCO skill hierarchy, led by information and communication technologies (icts). The single most important is digital data processing.
How hard is the move from data scientist to data analyst?
Its learning distance is 32.3 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.