Data Scientist
Även känt som: 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.
Kompetenser som ska mätas
Dessa är beteende- och förmågekonstruktionerna i denna profil. För varje konstruktion anges vilken frågehrmforce-frågeformulär som mäter den.
| Kompetenser som ska mätas | Målnivå | hrmforce instrument | Bedömningsmetod | Beteendeankare på målnivå |
|---|---|---|---|---|
| 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 Kompetens (50-ramverk): 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 Kompetens (50-ramverk): 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. |
Kort profil
De tio viktigaste kompetenserna i denna profil. Den fullständiga profilen med alla kompetenser, beteendeankare och utvärderingsmetoder finns i nedladdningsfilen.
| T | Kompetens | Målnivå | Vikt | Knockout | Bedömningsmetod |
|---|---|---|---|---|---|
| K | Basic statistical interpretation | N5 | 5 | ja | Knowledge test |
| A | Numerical reasoning | N4 | 5 | ja | Cognitive ability test |
| V | Data analysis | N4 | 5 | ja | Work sample test |
| V | Testing hypotheses | N4 | 5 | nej | Work sample test |
| V | Programming | N4 | 5 | ja | Work sample test |
| K | Machine learning fundamentals | N4 | 5 | ja | Knowledge test |
| V | Critical thinking and source evaluation | N4 | 4 | nej | Work sample test |
| V | Visual communication and data storytelling | N4 | 4 | nej | Work sample test |
| V | Instructing and explaining | N4 | 4 | nej | Work sample test |
| V | Data visualisation | N4 | 4 | nej | Work sample test |
Se alla 27 kompetenser i den fullständiga profilen
Bedömningsverktyg för denna tjänst
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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