IT, BI / Business Analysis, Science / Research

Data Scientist

Related positions: Data Scientist, Business Intelligence Analyst, Competitive Intelligence Analyst, Data Analyst, Intelligence Analyst, Market Intelligence Analyst, Market Intelligence Consultant, Strategic Business and Technology Intelligence Consultant, Strategist Clinical Data Management Director, CDM Director, Clinical Data Management Manager, CDM Manager, Clinical Data Manager, Clinical Informatics Manager, Data Deliverables Manager, Data Management Manager, Biometrician, Biostatistical Consultant, Biostatistician, Research Scientist, Statistical Scientist, Demographer, Mathematical Statistician, Psychometric Consultant, Quantitative Methodologist, Researcher, Statistical Analyst, Statistical Consultant, Statistical Reporting Analyst, Statistician

Overview

A data scientist is an expert in analyzing and interpreting complex data sets using statistical and computational methods. They use their expertise to extract insights and identify patterns that can help inform business decisions.

The main responsibilities of a data scientist may include collecting and processing large sets of data, performing statistical analysis and modeling, developing algorithms and machine learning models, and creating visualizations and reports to communicate insights to stakeholders.

Common tasks 

    TaskRelated trait(s)
    Collecting data from various sources and standardize datasets, ensuring data validity and reliability Methodical Precision  Data Excellence Drive
    Conducting statistical analyses Data Excellence Drive
    Collaborating with other teams to develop data-driven solutions Presentation Prowess   Altruistic Collaboration
    Identifying tools and statistical models to conduct data analysis Data Excellence Drive Analytical Innovation
    Communicating findings to technical and non-technical stakeholders Empathetic Listening 
    Staying up-to-date with developments in data science Continuous Learning Analytical Innovation Analytical Curiosity
    Managing and mentoring junior data analysts Empathetic Listening

    Soft skills measured by TraitForward

    TraitNo of QuestionsCronbach’s  alpha (α)
    Empathetic Listening80.71
    Can they truly understand and respond to others’ perspectives, needs, and unstated concerns when gathering requirements or communicating analytical findings?
    Methodical Precision120.83
    Can they maintain exceptional attention to detail while systematically following procedures to ensure accuracy and reliability in their analytical work?
    Continuous Learning70.83
    Do they demonstrate a genuine commitment to expanding their knowledge through regular reading, seeking challenging material, and efficiently processing new information in their field?
    Data Excellence Drive70.72
    Do they consistently demonstrate a commitment to exceeding standards in their data work, showing initiative, rapid learning, and a persistent drive for quality outcomes?
    Analytical Innovation100.82
    Can they generate original insights by connecting disparate data points and thinking beyond established analytical approaches?
    Analytical Curiosity80.74
    Do they demonstrate a genuine intellectual curiosity that drives them to dig deeper into data, continuously question findings, and find satisfaction in solving complex analytical problems?
    Presentation Prowess50.74
    Can they confidently and clearly present complex data insights to both technical and non-technical audiences?
    Analytical Precision60.70
    Can they demonstrate methodical thinking, careful evaluation of evidence, and thoughtful decision-making in their analytical work processes?
    Collaborative Excellence80.74
    Can they work effectively within teams by fostering inclusive participation, respecting group decisions, and actively supporting colleagues to achieve shared analytical goals?
    Altruistic Collaboration60.73
    Do they genuinely prioritize helping others and willingly sacrifice their time and resources to support colleagues’ success, even when there’s no personal benefit?
    Data Storytelling100.82
    Can they transform complex data into clear, compelling narratives that drive understanding and decision-making across diverse audiences?
    *Cronbach’s alpha coefficient (α) determines the extent to which the questions consistently measure each trait and it is expressed as a number ranging between 0 and 1 . Higher values indicate higher agreement between questions.  A value of α equal to greater than .7 indicates acceptable reliability or internal consistency.  For more information on the psychometric properties of the solution, please click here.

    Find out the psychometric properties for the Data Scientist Traitforward questionnaire

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