Episode 100: What Data Science Value Really Means

More from Value Driven Data Science All episodes →

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   E105 · 13 May 2026 · 29 min

   Episode 105: From AI Idea to Production Reality

   Organisations today have no shortage of AI ideas. What they lack is the ability to turn those ideas into production-ready systems that deliver real business value. For data scientists trying to get AI projects off the ground, understanding why that gap exists is as important as the technical work itself. In this episode, Santosh Kaveti joins Dr Genevieve Hayes to share what organisations consistently get wrong when embarking on AI initiatives, and what data scientists can do to help get it right. In this episode, you'll discover: Why organisations with great AI ideas still fail to deploy…

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   E104 · 6 May 2026 · 14 min

   Episode 104: [Value Boost] The Four Zones of AI Productivity for Data Scientists

   AI can get you to 60% of a finished output in minutes. But getting from 60% to 100% - the part where real insight lives - is where human expertise becomes the deciding factor. And the more expertise you bring, the further AI can take you. In this Value Boost episode, Brent Dykes joins Dr Genevieve Hayes to apply his Four Zones of AI Productivity framework to the insight generation process and explore what it means for data professionals who want to position themselves as strategic advisors. In this episode, you'll discover: The Four Zones of AI Productivity and how they apply to insight…

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   E103 · 29 Apr 2026 · 31 min

   Episode 103: The Art of the Actionable Insight

   Most data scientists have been in this situation: you spend hours analysing a dataset, return to your stakeholder with your findings, and are met with a polite "that's interesting" - before your work disappears into a drawer, never to be seen again. The problem usually isn't the analysis. It's that interesting observations and genuine insights are not the same thing. In this episode, Brent Dykes joins Dr Genevieve Hayes to share the frameworks behind identifying and communicating insights that actually move organisations to act. In this episode, you'll discover: What makes an insight an…

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   E102 · 22 Apr 2026 · 12 min

   Episode 102: [Value Boost] How Giving Away Your Work for Free Can Build Your Authority as a Data Scientist

   Building authority as a data professional doesn't require a large budget, a publisher, or even a large audience. But it does require a deliberate decision to share your thinking with the world and the patience to let that compound over time. In this Value Boost episode, Prof. Rob Hyndman joins Dr. Genevieve Hayes to share how selectively giving away his work for free helped him become one of the most cited and influential statisticians in the world, and what data professionals at any stage of their career can learn from that approach. In this episode, you'll discover: Why Rob decided to give…

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   E101 · 15 Apr 2026 · 28 min

   Episode 101: Why Traditional Statistics Still Matters in the Age of AI

   Data scientists today are under pressure to adopt the latest tools - machine learning, LLMs, generative AI. But in the rush to embrace what's new, many are leaving some of the most powerful analytical tools sitting on the shelf. Tools that handle something modern AI largely can't: uncertainty. In this episode, Prof. Rob Hyndman joins Dr. Genevieve Hayes to make the case for why rigorous statistical thinking remains indispensable in the age of AI, and what data scientists are giving up when they abandon it. In this episode, you'll discover: Why throwing data at an LLM is no substitute for…

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   E99 · 25 Mar 2026 · 11 min

   Episode 99: [Value Boost] Preventing ML Bias Before it Becomes a Problem

   Biased machine learning models don't just produce poor predictions. They can damage reputations, derail projects, and in high-stakes fields like healthcare, potentially cause real harm. Yet many data scientists don't check for bias until it's too late, missing the opportunity to address it at its source. In this Value Boost episode, Serg Masis joins Dr. Genevieve Hayes to share practical techniques for detecting and mitigating bias in machine learning models before they become major problems for you and your stakeholders. You'll discover: The most common bias patterns to watch for [01:32]…

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   E98 · 18 Mar 2026 · 25 min

   Episode 98: Building Trust in AI Through Model Interpretability

   When your machine learning model makes a decision that affects someone's medical treatment, financial security, or legal rights, "the algorithm said so" isn't good enough. Stakeholders need to understand why models make the decisions they do, and in high-stakes environments, model interpretability becomes the difference between AI adoption and AI rejection. In this episode, Serg Masis joins Dr. Genevieve Hayes to share practical strategies for building interpretable machine learning models that earn stakeholder trust and accelerate AI adoption within your organisation. You'll learn: The…