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This chapter explores how Russian data scientists learn and are taught technical skills. In the Moscow data science community, well-developed mathematical skills are almost universally treated as a given: a fundamental bedrock of established knowledge, upon which the specific methodological skills proper to data science can be scaffolded in the classroom and workplace. Beyond these concrete techniques, however, Russian data scientists are expected to cultivate more ephemeral forms of abstraction and judgement, which requires concrete experience developing applied research projects. This cultivation of technical skill is part of a broad commitment to lifelong learning shared by both academic and industrial researchers, and is allied to a widespread understanding of professional data scientists as constitutionally flexible workers. Rather than the product of a precarious labour market, however, I argue that my informants’ twin commitments to flexibility and lifelong learning are inextricable from their scientific and intellectual ethos.
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