For data scientists and engineers, soft skills for the modern world are not the old Trivium — rhetoric, logic, and grammar. My view on the set of skills that allow you to navigate complexity in the modern world, common for engineers, architects and data scientists:
- Systems Engineering (Thinking) — the ability to identify and select own system of interest, the operational environment, emergent properties, processes and lifecycle. See INCOSE material and ISO 42010.
- The ability to identify domains, stakeholders, concerns and their needs/requirements. See INCOSE material, IEEE 15288:2015 and NIST standard for Cyber-Physical Systems.
- The ability to formulate a hypothesis with supported measurements (see “Feynman on Scientific Method”)
- Stakeholder management: To work through conflicting goals and requirements — Theory of Constraint (Thinking Tools), see a lot of material in the TOC community by E.Goldratt, E.Schragenheim and many others. For a short introduction, see Clark Ching “Bottleneck Rules”.
- Conflict resolution technical — i.e. metal shall be soft and hard. See TRIZ with variations — Triz+, BioTRIZ.
The above requires the base ability to work productively within a given time — GTD/Superfocus/Pomodoro, and work with long text — Zettelkasten, which leads to identifying and building taxonomy and ontology of own concepts.
When focused on old Trivium, you can’t build complex systems or organisations (a system of systems), and you can’t make a good decision based on well-sounded arguments, to quote a conversation with one of my friends.
- Friend: “Agile/DevOps is a method of delivering things faster/better/cheaper. Would you like it?
- Me: Of course, yes.
- Friend: And I didn’t say anything meaningful until now.
Building complex and fruitful systems require precise communication and shared goals. Let’s focus on building complex, valuable, ethical systems.
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