Published Jun 10, 2021

Hilary Mason: The Rise of Data Science

Hilary Mason, CEO of Hidden Door, delves into the transformative rise of data science, offering insights into its integration in business, ethical practices, and evolving roles. She underscores the importance of combining quantitative and qualitative insights to drive impactful decisions while advocating for ethical vigilance within data teams.
Episode Highlights
World of DaaS logo

Popular Clips

Episode Highlights

  • Historical Changes

    , CEO of Hidden Door, reflects on the evolution of data science over the past decade. She highlights the shift from cumbersome infrastructure to scalable, cloud-based solutions that have significantly reduced friction in accessing computational resources 1. This transformation has enabled a broader range of professionals to engage in data science activities, often integrating these skills into roles like marketing and sales management 2.

    We live in this world of effortless, scalable, microservice cloud computing, which even ten years ago, you had to put a lot of effort into accessing the right compute for the kind of problem you wanted to solve.

    ---

    The democratization of data science tools has led to a dramatic increase in the number of data scientists, with noting a tenfold growth in the field 2.

       

    Future Predictions

    Looking ahead, envisions a future where data science skills become essential across all professional levels, potentially leading to a shift in how these roles are defined 2. She predicts that data science tools will become so integrated into various professions that the distinction between data scientists and other roles may blur 3.

    I believe that data skills will be a requisite skill in the executive suite and on down for everybody ten years from now.

    ---

    This evolution could result in a more data-oriented workforce, where even roles traditionally not associated with data science, like UI design, will require a deep understanding of machine learning and statistics 3.

       

    Tool Impact

    The impact of advanced tools on data science is profound, as explains how they have increased efficiency and expanded the scope of work accessible to non-specialists 4. These tools have reduced the time spent on data cleaning and preparation, allowing data scientists to focus more on analysis and innovation 5.

    Tools always have limits and they also tend to go wrong. But I think that you can accept that everyone should have the chance to do the work they want to do.

    ---

    Despite these advancements, emphasizes the continued need for specialists who can address complex problems where generic tools fall short 4.

Related Episodes