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  2. Analytical skill - Wikipedia

    en.wikipedia.org/wiki/Analytical_skill

    It is imperative in inferring information from data and adhering to a conclusion or decision from that data. Data analysis can stem from past or future data. Data analysis is an analytical skill, commonly adopted in business , as it allows organisations to become more efficient, internally and externally, solve complex problems and innovate .

  3. Résumé - Wikipedia

    en.wikipedia.org/wiki/Résumé

    A résumé or resume (or alternatively resumé), [a] [1] is a document created and used by a person to present their background, skills, and accomplishments. Résumés can be used for a variety of reasons, but most often are used to secure new jobs, whether in the same organization or another.

  4. Rachel Thomas (academic) - Wikipedia

    en.wikipedia.org/wiki/Rachel_Thomas_(academic)

    Thomas joined Exelon as a quantitative analyst, where she scraped internet data and built models to provide information to energy traders. [3] In 2013 Thomas joined Uber where she developed the driver interface and surge algorithms using machine learning. [4] She then became a teacher at Hackbright Academy, a school for women software engineers ...

  5. Data analysis - Wikipedia

    en.wikipedia.org/wiki/Data_analysis

    Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. The data may also be collected from sensors in the environment, including traffic cameras, satellites, recording devices, etc.

  6. T-shaped skills - Wikipedia

    en.wikipedia.org/wiki/T-shaped_skills

    The concept of T-shaped skills, or T-shaped persons is a metaphor used in job recruitment to describe the abilities of persons in the workforce.The vertical bar on the letter T represents the depth of related skills and expertise in a single field, whereas the horizontal bar is the ability to collaborate across disciplines with experts in other areas and to apply knowledge in areas of ...

  7. Data science - Wikipedia

    en.wikipedia.org/wiki/Data_science

    Data science also integrates domain knowledge from the underlying application domain (e.g., natural sciences, information technology, and medicine). [3] Data science is multifaceted and can be described as a science, a research paradigm, a research method, a discipline, a workflow, and a profession. [4]

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