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    Effective data scientists need to understand the workings of IT teams and identify the limits of truth in models, says Co-Founder and Chief Scientist at Ambiata.

    Tiberio was interviewed by Anthony Tockar on the Actuaries Institute’s podcast last month. This is the second episode from that conversation (the first explored the ethics of machine learning).

    If an actuary is working as a data scientist for a large organisation with millions of customers and complex internal IT legacy systems, being able to engage well with internal IT and data teams is critical. That means, as a first step, knowing their lingo.

    Data science combines both statistics and computer science. Actuaries are skilled in the former through their modelling and forecasting work, for the latter, they must upskill. As an actuary who transitioned into data science, Anthony said he spent most of his learning time on computer science. He highlights the importance of having a good handle on the underlying flow of data that informs the modelling.

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