Data scientist to meteorologist
A data scientist already meets 65% of what the meteorologist role asks for. The move turns on 10 required skills not yet in the profile.
47.6/ 100
1 How much of what a meteorologist 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 meteorologist role is recorded as needing, required and optional together. What these numbers mean.
Why this move works
A meteorologist role treats 30 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
- demonstrate disciplinary expertise
- develop professional network with researchers and scientists
What stands in the way is 10 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 35 skills that carry over, these are the ones fewest other occupations ask for. A meteorologist 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 quantitative analysis social sciences, journalism and information
- already held mathematical modelling natural sciences, mathematics and statistics
- already held execute analytical mathematical calculations information skills
- already held statistics natural sciences, mathematics and statistics
- already held manage findable accessible interoperable and reusable data information skills
- already held think abstractly communication, collaboration and creativity
All 35 carried skills, including the 30 the meteorologist role treats as required.
Table 3 · What you may need to learn
The 30 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 carry out meteorological research required
- still to learn review meteorological forecast data required
- still to learn use meteorological tools to forecast meteorological conditions required
- still to learn analyse weather forecast required
- still to learn apply scientific methods required
- still to learn apply statistical analysis techniques required
- still to learn use specialised computer models for weather forecasting required
- optional, not held collect weather-related data optional
- optional, not held conduct research on climate processes optional
- optional, not held develop models for weather forecast optional
- optional, not held manage meteorological database optional
- optional, not held study aerial photos optional
- still to learn climatology required
- still to learn mathematics required
- still to learn meteorology required
- optional, not held geographic information systems optional
- optional, not held hydrology optional
- optional, not held geography optional
- optional, not held oceanography optional
- optional, not held present during live broadcasts optional
- optional, not held assist scientific research optional
- optional, not held create weather maps optional
- optional, not held design graphics optional
- optional, not held design scientific equipment optional
- optional, not held write weather briefing optional
- optional, not held calibrate electronic instruments optional
- optional, not held operate meteorological instruments optional
- optional, not held operate remote sensing equipment optional
- optional, not held scientific research methodology optional
- optional, not held use geographic information systems optional
Table 4 · Where to start
The 3 entries a meteorologist role is least likely to hire without. The ordering is computed from the skill data, not from what pays.
- 01 carry out meteorological research practise this
- 02 review meteorological forecast data practise this
- 03 use meteorological tools to forecast meteorological conditions 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 35 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 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 apply blended learning skill
- already held mathematical modelling knowledge
- already held quantitative analysis knowledge
- already held statistics knowledge
- already held teach in academic or vocational contexts skill
20 supplementary skills, helpful but not required
- optional, not held geographic information systems optional
- optional, not held hydrology optional
- optional, not held present during live broadcasts optional
- optional, not held use geographic information systems optional
- optional, not held assist scientific research optional
- optional, not held calibrate electronic instruments optional
- optional, not held collect weather-related data optional
- optional, not held conduct research on climate processes optional
- optional, not held create weather maps optional
- optional, not held design graphics optional
- optional, not held design scientific equipment optional
- optional, not held develop models for weather forecast optional
- optional, not held geography optional
- optional, not held manage meteorological database optional
- optional, not held oceanography optional
- optional, not held operate meteorological instruments optional
- optional, not held operate remote sensing equipment optional
- optional, not held scientific research methodology optional
- optional, not held study aerial photos optional
- optional, not held write weather briefing optional
62 held skills the meteorologist role does not ask for
- not needed by the target role Hadoop knowledge
- not needed by the target role LDAP knowledge
- not needed by the target role LINQ knowledge
- not needed by the target role MDX knowledge
- not needed by the target role N1QL knowledge
- not needed by the target role SPARQL knowledge
- not needed by the target role XQuery 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 business intelligence knowledge
- not needed by the target role collect ICT data 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 create data models skill
- not needed by the target role data engineering knowledge
- not needed by the target role data ethics knowledge
- 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 quality assessment 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 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 image recognition knowledge
- not needed by the target role implement data quality processes 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 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
22 further entries not listed here
8 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 climatology required
- still to learn mathematics required
- still to learn meteorology required
- optional, not held geographic information systems optional
- optional, not held hydrology optional
- optional, not held geography optional
- optional, not held oceanography optional
- optional, not held scientific research methodology 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 meteorologist?
Yes, and it is a moderate move. A data scientist already covers 65% of what a meteorologist is expected to do: 35 skills carry over, 30 of which the meteorologist role treats as required.
What skills does a data scientist need to become a meteorologist?
10 required skills are missing, plus 20 optional ones. They fall into 6 areas of the ESCO skill hierarchy, led by information skills. The single most important is carry out meteorological research.
How hard is the move from data scientist to meteorologist?
Its learning distance is 47.6 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.