Podcast · Tech & Science

Value Driven Data Science

by Dr Genevieve Hayes · English · Tech & Science

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 lead

New episodes: Weekly
Typical length: 25 min
Latest: 14 Oct 2026
Language: English

Latest episode

14 Oct 2026 · 23 minNew

Episode 127: From Algorithms to Agents and What It Means for Data Science

The agentic AI era hasn't made algorithms irrelevant. It has just changed where data scientists need to focus their attention. And the data scientists who understand that distinction, and can explain it to stakeholders who don't, are the ones who will define what the profession looks like next. In this episode, Dr Imran Ahmad joins Dr Genevieve Hayes to explore the shift from algorithms to agents and what it means for how data scientists should be thinking about their role. You'll discover: How the data science toolkit has fundamentally shifted since the start of the AI era [02:09] The…

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Earlier episodes 29 most recent

E126 · 7 Oct 2026 · 21 min
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.…
E125 · 30 Sep 2026 · 27 min
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…
E124 · 23 Sep 2026 · 12 min
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…
E123 · 16 Sep 2026 · 25 min
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…
E122 · 9 Sep 2026 · 12 min
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…
E121 · 2 Sep 2026 · 30 min
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…
E120 · 26 Aug 2026 · 12 min
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…
E119 · 19 Aug 2026 · 29 min
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…
E118 · 12 Aug 2026 · 12 min
Episode 118: [Value Boost] Compounding Your Data Science Authority Beyond Blog Posts
A well-written blog post gets you noticed. But for data scientists who want to build authority that compounds over time, it's just the beginning. Every piece of writing is a potential stepping stone to something bigger - a conference talk, a book deal, or an opportunity you couldn't have anticipated. In this Value Boost episode, Cynthia Dunlop joins Dr Genevieve Hayes to explore how data scientists can convert blog writing into bigger opportunities and what it actually takes to make the leap from blog post to book. You'll discover: How conference organisers actually find their speakers — and…
E117 · 5 Aug 2026 · 25 min
Episode 117: Writing Your Way to Authority as a Data Scientist
For data scientists who want to build authority beyond their organisation, writing is one of the most powerful tools available. But in a world flooded with AI-generated content, simply publishing is no longer enough. The data scientists who stand out are the ones writing things no AI could have written. In this episode, Cynthia Dunlop joins Dr Genevieve Hayes to share practical frameworks for writing blog posts that stand out, build genuine authority and actually get read. You'll discover: Why AI-generated content has made personal experience more valuable than ever [05:10] The three Ps test…
E116 · 29 Jul 2026 · 14 min
Episode 116: [Value Boost] What Data Scientists Need to Know Before the AI Free Ride Ends
Right now, AI is cheap. But the companies providing it are losing billions of dollars a year and are expected to go public within the next 12 months. When they do, the price of intelligence is going up - and any organisation that has built its AI future entirely on rented intelligence is going to face a very unpleasant surprise. In this Value Boost episode, Nicholas Kelly joins Dr Genevieve Hayes to explore why organisations shouldn't be building their AI future entirely on frontier models, and what data professionals need to understand to be the strategic voice in the AI infrastructure…
E115 · 22 Jul 2026 · 28 min
Episode 115: Evolving Your Data Career for the AI Era
The AI era presents a choice for data professionals: wait to see what happens to your role, or get ahead of it and decide what it becomes. Nicholas Kelly made that choice two years ago, when a client told him ChatGPT could do 50% of what he did. What followed is a masterclass in proactive career evolution. In this episode, Nick joins Dr Genevieve Hayes to explore how data professionals can evolve their skills for the AI era, what that evolution looks like in practice, and why their existing expertise puts them in a stronger position than they might think. You'll discover: 1. How Nick evolved…
E114 · 15 Jul 2026 · 13 min
Episode 114: [Value Boost] The Four Conversations Every Data Scientist Needs to Master
For data scientists, getting a project approved is a sale. It might not feel like one and money might not change hands, but the dynamics are exactly the same. And like any sale, it goes a lot better if you go in with a plan. In this Value Boost episode, Blair Enns joins Dr Genevieve Hayes to explore how data professionals can use the Four Conversations framework to sell their expertise more effectively, whether as independent consultants or as employees within organisations. You'll discover: Why reputation is the most powerful sales tool a data professional has [04:33] How to stop behaving…
E113 · 8 Jul 2026 · 27 min
Episode 113: The Experts' AI Manifesto
Building genuine expertise takes years. And in the age of AI, losing it can happen gradually and almost invisibly, through small delegations that each seem reasonable in isolation but add up to something significant over time. In this episode, Blair Enns joins Dr Genevieve Hayes to explore how data professionals can use AI without compromising their hard-earned expertise and reputation. You'll discover: Why delegating to AI is always a trade-off [03:00] The crucial difference between writing to communicate and writing to think [08:40] Why you should orient yourself around the problems you…
E112 · 1 Jul 2026 · 16 min
Episode 112: [Value Boost] Lies, Damned Lies and Stakeholders
AI misinformation is a new problem. Misleading data is not. Long before anyone had heard of a hallucination, organisations were making bad decisions based on cherry-picked statistics, misunderstood averages, and numbers that confirmed what decision-makers already wanted to believe. In this Value Boost episode, Derek Gibson joins Dr Genevieve Hayes to explore how data professionals can help their stakeholders become better data sceptics and avoid being duped by misleading data long before it ever reaches an AI. In this episode, you'll discover: 1. The timeless data traps that catch even…
E111 · 24 Jun 2026 · 27 min
Episode 111: Building Your Defences Against AI Misinformation
AI doesn't lie - at least, not intentionally. It just sounds completely confident while filling in the gaps with whatever seems most plausible. And in a world where AI outputs are increasingly being used to inform high-stakes decisions, the ability to spot what's wrong, before it reaches a stakeholder, is becoming one of the most important skills a data professional can have. In this episode, Derek Gibson joins Dr Genevieve Hayes to share practical strategies for identifying unreliable AI outputs and building the defences necessary to keep AI-generated misinformation from reaching your…
E110 · 17 Jun 2026 · 17 min
Episode 110: [Value Boost] Why You Need Less Data Than You Think
In high-stakes decision-making, waiting for more data is often not an option. Yet many data scientists assume that without a large dataset, meaningful analysis is impossible. The good news is that rigorous, quantitative analysis is possible with far less data than most data scientists realise - in some cases with just a single datapoint. In this Value Boost episode, Douglas Hubbard joins Dr Genevieve Hayes to share practical techniques from How to Measure Anything that data scientists can start using right now to support high-stakes decisions when observations are scarce and every data point…
E109 · 10 Jun 2026 · 30 min
Episode 109: How to Measure Anything and Make Better Decisions
Data scientists are trained to work with large datasets. But the decisions that truly make or break an organisation are rarely the ones with large datasets behind them. They are the high-stakes, one-off decisions made under significant uncertainty - and most data scientists have no framework for handling them. In this episode, Douglas Hubbard joins Dr Genevieve Hayes to share how combining techniques from statistics, economics and decision theory can help data scientists tackle the problems that matter most. In this episode, you'll discover: What Applied Information Economics is and how it…
E108 · 3 Jun 2026 · 10 min
Episode 108: [Value Boost] How to Use AI Without Losing Your Edge
AI has the potential to dramatically expand what data scientists can do. But used without care, it also has the potential to quietly erode the expertise that makes them valuable in the first place. In this Value Boost episode, Tim Dietrich joins Dr Genevieve Hayes to explore how to stay on the right side of that line and what mindful AI use actually looks like in practice. In this episode, you'll discover: Why looking for problems to solve with AI is a warning sign [02:05] What happens when you use AI before you have the expertise to direct it [05:51] Why your AI interactions should be…
E107 · 27 May 2026 · 29 min
Episode 107: Building a Virtual Empire of AI Specialists
The question haunting every data scientist right now isn't whether AI will change their work, it's whether there will still be a place for them when it does. The answer, according to Tim Dietrich, isn't to compete with AI but to do something far more interesting with it - in his case, building a virtual team of over 100 AI specialists to dramatically expand what he is able to achieve. In this episode, Tim joins Dr Genevieve Hayes to share the principles and practicalities behind building a virtual AI team, and what data scientists can learn from his experience. In this episode, you'll…
E106 · 20 May 2026 · 12 min
Episode 106: [Value Boost] When AI Isn't the Answer
These days, every organisation wants to describe themselves as "AI-first". But in the rush to find opportunities to use AI, it can be easy to forget that AI isn't always the right answer. In this Value Boost episode, Santosh Kaveti joins Dr Genevieve Hayes to explore the situations where AI isn't the answer, how to recognise them, and how to have the conversation with stakeholders who are convinced it is. In this episode, you'll discover: The types of problems where AI consistently falls short [01:36] How to recognise when AI is the wrong tool for the job [04:46] Why most AI conversations…
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…
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…
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…
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…
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…
E100 · 8 Apr 2026 · 39 min
Episode 100: What Data Science Value Really Means
Over 100 episodes of conversations with world-class practitioners, a few ideas keep surfacing. Technical skill is necessary but never sufficient. The most valuable data professionals aren't the ones who build the best models - they're the ones who know which problems are worth solving. And the gap between those two things is where most data scientists are leaving value on the table. In this milestone episode, Dr. Genevieve Hayes reflects on her career journey and the conversations that helped her arrive at these conclusions, with Matt O'Mara turning the tables to put her in the hot seat. In…
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]…
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…

About Value Driven Data Science

Value Driven Data Science is a English tech & science podcast from Dr Genevieve Hayes. Melo plays each episode straight from the publisher's own feed — no ads added, no account needed — and remembers where you stopped, in this browser only.

Publisher: Dr Genevieve Hayes
Language: English
Category: Tech & Science
New episodes: Weekly
Typical length: 25 min
Latest episode: 14 Oct 2026
Feed: RSS — paste into any podcast app
Apple Podcasts: podcasts.apple.com/podcast/id1645444035

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