Value Driven Data Science

Dr Genevieve Hayes

Your stakeholders don’t want a better model. They want a better decision. Value Driven Data Science is a masterclass for data professionals ready to become strategic experts, valued for their judgement, not just the technical outputs they produce. Each week, Dr Genevieve Hayes speaks with leading thinkers and data practitioners who have already made that shift. You’ll leave every episode with an idea or framework you can start using right away. If you’re tired of being treated as just another data scientist, Value Driven Data Science will transform you into the trusted advisor your stakeholders ask for by name.

  1. 6 days ago

    Episode 126: Why AI Excels at Some Things and Sucks at Others

    Large language models excel at some tasks while struggling badly with other. At a time where it seems everyone is currently trying to make sense of AI, understanding and being able to explain exactly why this is the case, has become one of the most useful things data scientists can offer their stakeholders. In this special reverse interview episode, Lauren Pearl switches roles with Dr Genevieve Hayes to explore why LLMs work the way they do and what that means for anyone using AI in their work. You'll discover:1. What your training data tells you about what AI can and cannot do [05:05]2. Why high context problems are particularly hard for LLMs [06:28]3. How AI gives you the right answer for the wrong reason [08:08]4. Why some problems will always be beyond what LLMs can solve [14:22] Guest Bio Lauren Pearl is a business strategist, three-time founder and CFO advisor who helps start-up teams build data-driven businesses that thrive. She is also the resident start-up finance expert at NYU Stern’s Berkley Center for Entrepreneurship, where she teaches financial modelling to founders, and the co-host of The Growth-Minded CFO podcast. Links Connect with Lauren on LinkedInSubscribe to The Daily CFO newsletterConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

  2. 30 Sept

    Episode 125: The AI Chicken Nugget Problem

    Building something valuable with AI doesn't automatically make you valuable. If the value sits in your creation and your employer owns your creation, you're the one who's dispensable, not the thing you built. This is the AI chicken nugget problem and many data scientists who are impacted by it haven't even realised it yet. In this episode, Lauren Pearl joins Dr Genevieve Hayes to explore where real expertise still lives in the age of AI and what data scientists should actually be focusing on to build a sustainable career. You'll discover: What the AI chicken nugget problem is and why it matters [02:31]Why vibe coding is not a rare skill and never will be [05:12]Why obsessing over something rare and valuable is your best career bet [17:17]The skills worth investing in for a sustainable career [22:18]Guest Bio Lauren Pearl is a business strategist, three-time founder and CFO advisor who helps start-up teams build data-driven businesses that thrive. She is also the resident start-up finance expert at NYU Stern’s Berkley Center for Entrepreneurship, where she teaches financial modelling to founders, and the co-host of The Growth-Minded CFO podcast. Links Connect with Lauren on LinkedInSubscribe to The Daily CFO newsletterConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

  3. 23 Sept

    Episode 124: [Value Boost] 8 Disciplines Every Decision System Needs

    Machine learning is what most data scientists know best. But when it comes to building systems that enable better decision-making, machine learning is just one piece of the puzzle. And leaning on it too much can leave your entire decision system exposed. In this Value Boost episode, Adam DeJans Jr joins Dr Genevieve Hayes to walk through the eight disciplines that make up the modern decision stack and where data scientists should focus to close the gaps in their own skill set. You'll discover: The eight disciplines that make up the modern decision stack [01:24]The most overlooked layer in most decision systems [04:47]Why optimization textbooks are teaching data scientists the wrong things [06:17]What to learn next if you want to build better decision systems [09:45]Guest Bio Adam DeJans Jr. is a decision scientist and optimisation expert who has led high-stakes decision systems in complex, uncertain environments, at companies including Amazon, Toyota and Ford. He is the co-founder of AI and decision intelligence consultancy Bit Bros and co-author of The Decision Factory: A Novel About Decisions Under Uncertainty. Links Connect with Adam on LinkedInBit Bros websiteConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

  4. 16 Sept

    Episode 123: How to Build a Decision Factory Inside Your Organisation

    Data scientists are trained to build better models. But stakeholders don't wake up hoping for a better model. They wake up hoping to make better decisions. And the gap between those two things is where most data science value quietly disappears. In this episode, Adam DeJans Jr joins Dr Genevieve Hayes to share what it actually looks like when an organisation stops optimising for better predictions and starts building systems that enable better decisions - that is, decision factories. You'll discover: What separates a decision factory from a machine learning pipeline [02:11]Why uncertainty is an input into good decision making [10:51]How to test a decision policy before it costs you real money [12:11]Why giving stakeholders options beats giving them the optimal solution [18:48]Guest Bio Adam DeJans Jr. is a decision scientist and optimisation expert who has led high-stakes decision systems in complex, uncertain environments, at companies including Amazon, Toyota and Ford. He is the co-founder of AI and decision intelligence consultancy Bit Bros and co-author of The Decision Factory: A Novel About Decisions Under Uncertainty. Links Connect with Adam on LinkedInBit Bros websiteConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

  5. 9 Sept

    Episode 122: [Value Boost] 4 Questions Every Data Scientist Should Ask About AI Strategy

    Choosing which AI tools to buy is the easy part of an AI strategy. The hard part - and the part most organisations are ignoring - is everything that sits beneath the tools, from platform and inference decisions to hardware and sovereignty. In this Value Boost episode, Victor Coimbra joins Dr Genevieve Hayes to share his framework for cutting through the noise of AI tool selection to the strategic decisions that will actually determine whether an organisation's AI future succeeds or fails. You'll discover: The four layers of an agentic AI strategy and why most organisations only think about one [01:53]The three symptoms that signal an organisation's AI strategy is breaking down [05:52]The four questions that reveal what an organisation's AI strategy is actually missing [08:21]The one question data scientists should lead with when advising stakeholders on AI [10:43]Guest Bio Victor Coimbra is a Partner and CTO at Artefact, the world’s largest pure-play AI consulting firm and co-founded the firm’s Latin American operations. In 2024, he was recognised in the Forbes 30 Under 30 Brazil list for his outstanding contributions to AI innovation. Links Connect with Victor on LinkedInVictor's article on the four-layer frameworkArtefact websiteConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

  6. 2 Sept

    Episode 121: What Hybrid Agentic AI Organisations Mean for Data Science

    The debate about whether AI will replace human workers has already been settled - not by academics or futurists, but by the organisations that fired their humans, discovered AI couldn't do what they needed, and quietly hired them back. The future isn't AI replacing humans. It's humans and AI working together in ways that neither could manage alone. In this episode, Victor Coimbra joins Dr Genevieve Hayes to share what hybrid agentic organisations actually look like in practice, and what data scientists need to do to position themselves at the centre of them. You'll discover: Why thinking of AI as a tool rather than a coworker is the mindset holding most organisations back [03:58]The four archetypes that determine which tasks belong to humans and which to agents [08:17]How AI is turning data scientists back into scientists [18:24]The two skills that will define an indispensable data scientist in a hybrid organisation [27:01]Guest Bio Victor Coimbra is a Partner and CTO at Artefact, the world’s largest pure-play AI consulting firm and co-founded the firm’s Latin American operations. In 2024, he was recognised in the Forbes 30 Under 30 Brazil list for his outstanding contributions to AI innovation. Links Connect with Victor on LinkedInArtefact websiteConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

  7. 26 Aug

    Episode 120: [Value Boost] The AI Silent Correctness Problem

    AI hallucinations get all the attention. But hallucinations are relatively easy to catch because the output is obviously wrong. The failure mode that should worry data scientists more is when the agent uses facts that are true to draw conclusions that are false, producing outputs that look perfectly fine. This is known as silent correctness. In this Value Boost episode, Jia Huang joins Dr Genevieve Hayes to explore why silent correctness is the most dangerous failure mode in agentic AI systems and what data scientists can do to catch it before it causes serious harm. You'll discover: Why silent correctness is harder to catch than a hallucination [04:17]Why sampling and auditing are non-negotiable in agentic systems [07:09]Four techniques data scientists can use to catch silent failures [09:28]The one safeguard every agentic AI system should have [11:10]Guest Bio Jia Huang is a lead research engineer at A*STAR, Singapore's Agency for Science, Technology and Research, and is the author of multiple books on AI engineering and agent design, including Designing AI Agents and RAG from First Principles. His work focuses on turning agentic AI from impressive demos into reliable, auditable, and value-producing engineering systems. Links Connect with Jia on LinkedInFollow Jia on SubstackAgent Design Pattern Society (ADPS) websiteJia's AI agent design position paperConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

  8. 19 Aug

    Episode 119: Rewiring Your Data Science Thinking for the Agentic AI Era

    The shift to agentic AI doesn't make data science skills obsolete. But it does require data scientists to rewire how they think about familiar concepts, such as uncertainty, model evaluation and accountability, in their work. In this episode, Jia Huang joins Dr Genevieve Hayes to explore what that rewiring actually looks like, and why data scientists are better placed than almost any other profession to make it. You'll discover: Why data scientists are better prepared for the agentic AI era than they might think [03:00]How the data scientist's role is shifting from analyst to system designer [06:37]The three types of uncertainty in agentic AI systems [11:58]Why context engineering is the new feature engineering [23:19]Guest Bio Jia Huang is a lead research engineer at A*STAR, Singapore's Agency for Science, Technology and Research, and is the author of multiple books on AI engineering and agent design, including Designing AI Agents and RAG from First Principles. His work focuses on turning agentic AI from impressive demos into reliable, auditable, and value-producing engineering systems. Links Connect with Jia on LinkedInFollow Jia on SubstackAgent Design Pattern Society (ADPS) websiteJia's AI agent design position paperConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE

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Ratings & Reviews

5
out of 5
2 Ratings

About

Your stakeholders don’t want a better model. They want a better decision. Value Driven Data Science is a masterclass for data professionals ready to become strategic experts, valued for their judgement, not just the technical outputs they produce. Each week, Dr Genevieve Hayes speaks with leading thinkers and data practitioners who have already made that shift. You’ll leave every episode with an idea or framework you can start using right away. If you’re tired of being treated as just another data scientist, Value Driven Data Science will transform you into the trusted advisor your stakeholders ask for by name.

Information

  • Creator
    Dr Genevieve Hayes
  • Years Active
    2022 - 2026
  • Episodes
    126
  • Rating
    Clean
  • Copyright
    © 2026 Genevieve Hayes Consulting
  • Show Website
    Value Driven Data Science

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