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

data analysttodata scientist

A data analyst already meets 47% of what the data scientist role asks for. The move turns on 36 required skills not yet in the profile.

From data analyst
47%
Overlap1
To data scientist
51 Skills carried over
36 Required, not held
68.5 Difficulty2
adjacent 0–30
moderate 30–55
substantial 55–75
career change 75–100
this move, 68.5

This move: 68.5 of 100 · substantial

1 Share of the data scientist role’s weighted skill requirement already met by the data analyst 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.

Table 2

Table 2 · What you already bring

Of the 51 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 analyst background worth leading with.

Skill the target role also needs Area
  • 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 normalise data working with computers
  • already held statistical modeling techniques natural sciences, mathematics and statistics

All 51 carried skills, including the 27 the data scientist role treats as required.

Table 3

Table 3 · What you would need to learn

The 46 missing skills fall into 9 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, 4 supplementary
  • required, not held design database scheme required
  • required, not held manage intellectual property rights required
  • required, not held communicate with a non-scientific audience 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 design database in the cloud optional
  • 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 11 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 conduct research across disciplines required
  • required, not held demonstrate disciplinary expertise required
  • required, not held integrate gender dimension in research 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
03 working with computers 4 required, 1 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
  • optional, not held manage ICT data classification optional
04 generic programmes and qualifications 2 required
  • required, not held empirical analysis required
  • required, not held scientific literature required
05 management skills 2 required
  • required, not held manage personal professional development required
  • required, not held perform project management required
06 natural sciences, mathematics and statistics 1 required, 1 supplementary
  • required, not held mathematical modelling required
  • optional, not held computational biology optional

3 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 51 skills that carry over
Skill Type
  • 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 science knowledge
  • already held data visualisation software knowledge
  • already held deliver visual presentation of data 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 interpret current data skill
  • already held manage data collection systems skill
  • already held normalise data skill
  • already held online analytical processing knowledge
  • 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 statistical modeling techniques knowledge
  • already held statistics 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 business analytics knowledge
  • already held business intelligence knowledge
  • already held create data models skill
  • already held data quality assessment knowledge
  • already held define data quality criteria skill
  • already held healthcare analytics knowledge
  • already held image recognition knowledge
  • already held integrate ICT data skill
  • already held make data-driven decisions skill
  • already held manage data skill
  • already held marketing analytics knowledge
  • already held multidisciplinary research knowledge
  • already held perform data mining skill
  • already held research design knowledge
  • already held social network analysis knowledge
  • already held unstructured data knowledge
  • already held use spreadsheets software skill
The 3 learning areas not shown above
Skill to acquire Tier
07 social sciences, journalism and information 1 required, 1 supplementary
  • required, not held quantitative analysis required
  • optional, not held digital curation optional
08 information and communication technologies (icts) 2 supplementary
  • optional, not held computer simulation optional
  • optional, not held scientific computing optional
09 engineering, manufacturing and construction 1 supplementary
  • optional, not held state estimation optional
10 supplementary skills, helpful but not required
Skill to acquire Tier
  • optional, not held digital curation optional
  • optional, not held computational biology optional
  • optional, not held design database in the cloud optional
  • optional, not held manage ICT data architecture optional
  • optional, not held manage ICT data classification optional
  • optional, not held apply blended learning optional
  • optional, not held computer simulation optional
  • optional, not held scientific computing optional
  • optional, not held state estimation optional
  • optional, not held teach in academic or vocational contexts optional
16 held skills the data scientist role does not ask for
Skill Type
  • not needed by the target role analyse big data skill
  • not needed by the target role apply statistical analysis techniques skill
  • not needed by the target role cloud technologies knowledge
  • not needed by the target role data storage knowledge
  • not needed by the target role database knowledge
  • not needed by the target role digital data processing skill
  • not needed by the target role documentation types knowledge
  • not needed by the target role game theory knowledge
  • not needed by the target role gather data for forensic purposes skill
  • not needed by the target role information architecture knowledge
  • not needed by the target role information confidentiality knowledge
  • not needed by the target role information structure knowledge
  • not needed by the target role manage cloud data and storage skill
  • not needed by the target role manage quantitative data skill
  • not needed by the target role store digital data and systems skill
  • not needed by the target role web analytics knowledge
9 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 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 computational biology optional
  • optional, not held computer simulation optional
  • optional, not held scientific computing optional
  • optional, not held state estimation optional
Index

Other moves recorded from data analyst

Full index of moves from data analyst

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.