Where is the data science skill in SFIA?

SFIA describes all the skills needed to support data science practices - it does not have a single skilled named Data science.

The SFIA framework represents "Data Science" with a broad and rich range of professional skills and generic attributes.

  • There are many SFIA skills and attributes at multiple levels which organisations can align to their Data Scientist roles. 
  • SFIA's granular design enables you to align skill and proficiency levels to the overall practice of Data Science in your organisations. This emphasises that Data Scientists are not the only roles needed to perform good Data Science, and related roles also have distinct or overlapping professional skills.  SFIA describes them all.

The SFIA skill aligned with the statistics and programming foundation of data science is Analytics.  SFIA describes Analytics at level 3, 4, 5 6 & 7.

Analytics INAN
The application of mathematics, statistics, predictive modeling and machine-learning techniques to discover meaningful patterns and knowledge in recorded data. Analysis of data with high volumes, velocities and variety (numbers, symbols, text, sound and image). Development of forward-looking, predictive, real-time, model-based insights to create value and drive effective decision-making. The identification, validation and exploitation of internal and external data sets generated from a diverse range of processes.

In addition - there are other related skills to consider for a Data Scientist's role...

SFIA also describes the generic attributes which relate to professionals at all levels in the workplace ( leading, managing or doing Data Science). These have responsibility levels from 1 (entry level) to 7 (strategic leadership).

  • Autonomy
  • Influence
  • Complexity
  • Knowledge
  • Business Skills
    • Communication
    • Personal Work Scheduling
    • Teamwork or otherwise
    • Problem Solving
    • Ethics, Code of Conduct
    • Security