Data scientist to computer scientist
A data scientist already meets 64% of what the computer scientist role asks for. The move turns on 14 required skills not yet in the profile.
52.3/ 100
1 How much of what a computer scientist 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 computer scientist role is recorded as needing, required and optional together. What these numbers mean.
Why this move works
A computer scientist role treats 31 of its required skills as things a data scientist already does. You would walk in with these on day one.
- apply for research funding
- apply research ethics and scientific integrity principles in research activities
- communicate with a non-scientific audience
- conduct research across disciplines
- data science
- demonstrate disciplinary expertise
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 · What you already bring
Of the 54 skills that carry over, these are the ones fewest other occupations ask for. A computer scientist 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 scientific computing information and communication technologies (icts)
- already held image recognition information and communication technologies (icts)
- already held computational biology natural sciences, mathematics and statistics
- already held information categorisation social sciences, journalism and information
- already held data engineering information and communication technologies (icts)
- already held data science information and communication technologies (icts)
All 54 carried skills, including the 31 the computer scientist role treats as required.
Table 3 · What you may need to learn
The 36 missing skills fall into 10 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 execute ICT user research activities required
- still to learn apply statistical analysis techniques required
- still to learn conduct literature research required
- still to learn conduct qualitative research required
- still to learn conduct quantitative research required
- still to learn conduct scholarly research required
- still to learn synthesise research publications required
- optional, not held process data optional
- still to learn apply reverse engineering required
- still to learn use an application-specific interface required
- still to learn use back-up and recovery tools required
- optional, not held implement anti-virus software optional
- optional, not held use query languages optional
- optional, not held develop computer vision system optional
- optional, not held use presentation software optional
- still to learn conduct research interview required
- still to learn write research proposals required
- optional, not held innovate in ICT optional
- optional, not held create solutions to problems optional
- optional, not held develop professional network optional
- still to learn scientific research methodology required
- still to learn define technology strategy required
- optional, not held Apache Tomcat optional
- optional, not held JavaScript Framework optional
- optional, not held NoSQL optional
- optional, not held SQL optional
- optional, not held cognitive computing optional
- optional, not held quantum computing optional
- optional, not held software frameworks optional
4 further areas in the appendix
Table 4 · Where to start
The 3 entries a computer scientist role is least likely to hire without. The ordering is computed from the skill data, not from what pays.
- 01 apply reverse engineering practise this
- 02 define technology strategy practise this
- 03 execute ICT user research activities 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 54 skills that carry over
- already held apply for research funding skill
- already held apply research ethics and scientific integrity principles in research activities skill
- already held communicate with a non-scientific audience skill
- already held conduct research across disciplines skill
- already held data science knowledge
- already held demonstrate disciplinary expertise skill
- already held develop professional network with researchers and scientists skill
- already held disseminate results to the scientific community skill
- already held draft scientific or academic papers and technical documentation skill
- already held evaluate research activities skill
- already held execute analytical mathematical calculations skill
- already held increase the impact of science on policy and society skill
- already held integrate gender dimension in research skill
- already held interact professionally in research and professional environments skill
- already held manage findable accessible interoperable and reusable data skill
- already held manage intellectual property rights skill
- already held manage open publications skill
- already held manage personal professional development skill
- already held manage research data skill
- already held mentor individuals skill
- already held operate open source software skill
- already held perform project management skill
- already held perform scientific research skill
- already held promote open innovation in research skill
- already held promote the participation of citizens in scientific and research activities skill
- already held promote the transfer of knowledge skill
- already held publish academic research skill
- already held speak different languages skill
- already held synthesise information skill
- already held think abstractly skill
- already held write scientific publications 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 apply blended learning skill
- already held business intelligence knowledge
- already held computational biology knowledge
- already held computer simulation knowledge
- already held data engineering knowledge
- already held data mining knowledge
- already held image recognition knowledge
- already held information categorisation knowledge
- already held information extraction knowledge
- already held perform data mining skill
- already held query languages knowledge
- already held report analysis results skill
- already held resource description framework query language knowledge
- already held scientific computing knowledge
- already held teach in academic or vocational contexts skill
- already held unstructured data knowledge
- already held use spreadsheets software skill
The 4 learning areas not shown above
- optional, not held documentation types optional
- optional, not held behavioural science optional
- optional, not held digitization optional
- optional, not held innovation processes optional
- optional, not held operational research optional
- optional, not held emergent technologies optional
- optional, not held mathematical physics optional
22 supplementary skills, helpful but not required
- optional, not held Apache Tomcat optional
- optional, not held JavaScript Framework optional
- optional, not held NoSQL optional
- optional, not held SQL optional
- optional, not held cognitive computing optional
- optional, not held documentation types optional
- optional, not held implement anti-virus software optional
- optional, not held innovate in ICT optional
- optional, not held innovation processes optional
- optional, not held mathematical physics optional
- optional, not held quantum computing optional
- optional, not held software frameworks optional
- optional, not held use query languages optional
- optional, not held behavioural science optional
- optional, not held create solutions to problems optional
- optional, not held develop computer vision system optional
- optional, not held develop professional network optional
- optional, not held digitization optional
- optional, not held emergent technologies optional
- optional, not held operational research optional
- optional, not held process data optional
- optional, not held use presentation software optional
43 held skills the computer scientist role does not ask for
- not needed by the target role Hadoop knowledge
- 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 collect ICT data skill
- not needed by the target role create data models skill
- not needed by the target role data ethics knowledge
- not needed by the target role data models knowledge
- not needed by the target role data quality assessment knowledge
- not needed by the target role data visualisation software knowledge
- not needed by the target role define data quality criteria skill
- not needed by the target role deliver visual presentation of data 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 digital curation knowledge
- not needed by the target role empirical analysis knowledge
- not needed by the target role establish data processes skill
- not needed by the target role handle data samples skill
- not needed by the target role healthcare analytics knowledge
- not needed by the target role implement data quality processes skill
- not needed by the target role integrate ICT data 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 skill
- not needed by the target role manage data collection systems skill
- not needed by the target role marketing analytics knowledge
- not needed by the target role mathematical modelling knowledge
- not needed by the target role multidisciplinary research knowledge
- not needed by the target role normalise data skill
- not needed by the target role online analytical processing knowledge
- not needed by the target role perform data cleansing 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 scientific literature knowledge
- not needed by the target role social network analysis knowledge
- not needed by the target role state estimation knowledge
- not needed by the target role statistical modeling techniques knowledge
- not needed by the target role statistics knowledge
3 further entries not listed here
15 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 scientific research methodology required
- optional, not held Apache Tomcat optional
- optional, not held JavaScript Framework optional
- optional, not held NoSQL optional
- optional, not held SQL optional
- optional, not held cognitive computing optional
- optional, not held documentation types optional
- optional, not held innovation processes optional
- optional, not held mathematical physics optional
- optional, not held quantum computing optional
- optional, not held software frameworks optional
- optional, not held behavioural science optional
- optional, not held digitization optional
- optional, not held emergent technologies optional
- optional, not held operational research 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
- data quality specialist 66% covered · moderate
- seismologist 66% covered · moderate
Common questions about this move
Can a data scientist become a computer scientist?
Yes, and it is a moderate move. A data scientist already covers 64% of what a computer scientist is expected to do: 54 skills carry over, 31 of which the computer scientist role treats as required.
What skills does a data scientist need to become a computer scientist?
14 required skills are missing, plus 22 optional ones. They fall into 10 areas of the ESCO skill hierarchy, led by information skills. The single most important is apply reverse engineering.
How hard is the move from data scientist to computer scientist?
Its learning distance is 52.3 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.