Data Scientist
Also known as: Applied Scientist · Advanced Analytics Specialist
Develops statistical and learning models on business data, tests their reliability and translates outcomes into usable conclusions.
The data scientist frames a research question, chooses a method and substantiates how certain an outcome is before decisions rest on it. Unlike the machine learning engineer, the task largely ends with a demonstrably working model rather than keeping it running in production. Selection targets algorithms and programming language, while the real bottleneck is explainability: a model the client neither understands nor can check is either not used or used without anyone knowing the assumptions.
Competencies to measure
These are the behavioural and ability constructs in this profile. Each one shows which hrmforce questionnaire measures it.
| Competencies to measure | Target level | hrmforce instrument | Assessment method | Behavioural anchor at target level |
|---|---|---|---|---|
| Numerical reasoning Knockout | N4 | Ability Scan | Cognitive ability test | Combines two data sources, calculates the development over time and explains which calculation step leads to which result. |
| Curiosity and exploring Competency (50-framework): Learning Ability | N3 | Big Fifty, 15PF, Motivation | Personality questionnaire | Gathers information on new methods outside the own team and brings findings into the work meeting unprompted. |
| Dealing with ambiguity Competency (50-framework): Flexibility | N3 | Big Fifty, Mental Resilience (4C), Competency Check | Situational Judgement Test | Formulates explicit assumptions when information is missing, proceeds on that basis and revises the approach once new data arrives. |
Short profile
The ten heaviest skills in this profile. The full profile with every skill, behavioural anchor and assessment method is in the download.
| T | Skill | Target level | Weight | Knockout | Assessment method |
|---|---|---|---|---|---|
| K | Basic statistical interpretation | N5 | 5 | yes | Knowledge test |
| A | Numerical reasoning | N4 | 5 | yes | Cognitive ability test |
| V | Data analysis | N4 | 5 | yes | Work sample test |
| V | Testing hypotheses | N4 | 5 | no | Work sample test |
| V | Programming | N4 | 5 | yes | Work sample test |
| K | Machine learning fundamentals | N4 | 5 | yes | Knowledge test |
| V | Critical thinking and source evaluation | N4 | 4 | no | Work sample test |
| V | Visual communication and data storytelling | N4 | 4 | no | Work sample test |
| V | Instructing and explaining | N4 | 4 | no | Work sample test |
| V | Data visualisation | N4 | 4 | no | Work sample test |
See all 27 skills in the full profile
Assessment instruments for this job
Work sample test
Representative work sample under standardized conditions
Knowledge test (client-specific)
Professional knowledge test, customized for each client
Competency Check
Behavioral-Level Competency Assessment
Portfolio
Evaluation of prior work against fixed criteria
Structured interview
Behavioral interview with a fixed structure
Ability Scan
Aptitude Test: Verbal, Numerical, and Abstract Reasoning Skills
360 Feedback
Multiple assessments based on behavioral anchors
Big Fifty
Personality questionnaire, 150 items, 25 factors
15PF
Personality Profile, a shorter alternative to the Big Fifty
Motivation
Drivers and sources of motivation
Mental Resilience (4C)
Mental Resilience According to the 4C Model
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