Table 1Transition record

data scientisttobiometrician

A data scientist already meets 69% of what the biometrician role asks for. The move turns on 8 required skills not yet in the profile.

From data scientist

69%

Overlap1

To biometrician

40 Skills carried over

8 Required, not held

45 Difficulty2

adjacent 0–30

moderate 30–55

substantial 55–75

career change 75–100

this move, 45

This move: 45 of 100 · moderate

1 Share of the biometrician role’s weighted skill requirement already met by the data scientist 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 40 skills that carry over, these are the ones fewest other occupations ask for. A biometrician 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.

Skill the target role also needs Area

already held statistical modeling techniques natural sciences, mathematics and statistics
already held computational biology natural sciences, mathematics and statistics
already held interpret current data information skills
already held manage data collection systems information skills
already held data science information and communication technologies (icts)
already held multidisciplinary research generic programmes and qualifications

All 40 carried skills, including the 36 the biometrician role treats as required.

Table 3

Table 3 · What you would need to learn

The 33 missing skills fall into 8 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 natural sciences, mathematics and statistics 3 required, 5 supplementary

required, not held biometrics required
required, not held life sciences required
required, not held mathematics required

optional, not held computational chemistry optional
optional, not held proteomics optional
optional, not held stem cells optional
optional, not held biology optional
optional, not held statistical analysis system software optional

02 information skills 3 required, 4 supplementary

required, not held plan research process required
required, not held apply statistical analysis techniques required
required, not held develop scientific research protocols required

optional, not held develop scientific theories optional
optional, not held conduct public surveys optional
optional, not held gather experimental data optional
optional, not held manage database optional

03 information and communication technologies (icts) 1 required, 2 supplementary

required, not held scientific modelling required

optional, not held SAS language optional
optional, not held screen reader optional

04 education 1 required

required, not held scientific research methodology required

05 communication, collaboration and creativity 10 supplementary

optional, not held contribute to development of biometric systems optional
optional, not held create software design optional
optional, not held advise on legislative acts optional
optional, not held apply teaching strategies optional
optional, not held assist in clinical trials optional
optional, not held assist scientific research optional
optional, not held prepare lesson content optional
optional, not held provide lesson materials optional
optional, not held write research proposals optional
optional, not held write work-related reports optional

06 working with computers 2 supplementary

optional, not held develop statistical software optional
optional, not held prepare visual data optional

2 further areas in the appendix

Table 4

Table 4 · Where to start

The 3 entries a biometrician 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 40 skills that carry over

Skill Type

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 computational biology knowledge
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 interpret current data 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 multidisciplinary research knowledge
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 research design knowledge
already held speak different languages skill
already held statistics knowledge
already held synthesise information skill
already held think abstractly skill
already held write scientific publications skill
already held apply blended learning skill
already held manage data collection systems skill
already held statistical modeling techniques knowledge
already held teach in academic or vocational contexts skill

The 2 learning areas not shown above

Skill to acquire Tier

07 assisting and caring 1 supplementary

optional, not held assess environmental impact optional

08 management skills 1 supplementary

optional, not held prepare exercise session optional

25 supplementary skills, helpful but not required

Skill to acquire Tier

optional, not held contribute to development of biometric systems optional
optional, not held SAS language optional
optional, not held computational chemistry optional
optional, not held create software design optional
optional, not held develop scientific theories optional
optional, not held prepare exercise session optional
optional, not held proteomics optional
optional, not held stem cells optional
optional, not held advise on legislative acts optional
optional, not held apply teaching strategies optional
optional, not held assess environmental impact optional
optional, not held assist in clinical trials optional
optional, not held assist scientific research optional
optional, not held biology optional
optional, not held conduct public surveys optional
optional, not held develop statistical software optional
optional, not held gather experimental data optional
optional, not held manage database optional
optional, not held prepare lesson content optional
optional, not held prepare visual data optional
optional, not held provide lesson materials optional
optional, not held screen reader optional
optional, not held statistical analysis system software optional
optional, not held write research proposals optional
optional, not held write work-related reports optional

57 held skills the biometrician role does not ask for

Skill Type

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 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 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 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 marketing analytics knowledge
not needed by the target role mathematical modelling knowledge

17 further entries not listed here

12 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 biometrics required
required, not held life sciences required
required, not held mathematics required
required, not held scientific modelling required
required, not held scientific research methodology required
optional, not held SAS language optional
optional, not held computational chemistry optional
optional, not held proteomics optional
optional, not held stem cells optional
optional, not held biology optional
optional, not held screen reader optional
optional, not held statistical analysis system software optional

Index

Other moves recorded from data scientist

Full index of moves from data scientist

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.