Value Driven Data Science
by Dr Genevieve Hayes
Latest episode
Episode 129: Building Digital Twins Executives Can Trust
Episode 129: Building Digital Twins Executives Can Trust
About this podcast
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.
Episodes
The newest 20 of 129 episodes
- Episode 129: Building Digital Twins Executives Can Trust · 27 min · Episode 129When the cost of failure is low, experimentation is often the best way to make decisions. But when a wrong call could cost millions or endanger lives, you need an entirely…
- Episode 128: [Value Boost] The Three Types of Memory Every AI Agent Needs · 13 min · Episode 128One of the most frustrating things about working with AI is when it seems to suddenly forget everything it knew about you and your work. This is annoying when using AI chatbots…
- Episode 127: From Algorithms to Agents and What It Means for Data Science · 23 min · Episode 127The 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…
- Episode 126: Why AI Excels at Some Things and Sucks at Others · 21 min · Episode 126Large 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…
- Episode 125: The AI Chicken Nugget Problem · 27 min · Episode 125Building 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…
- Episode 124: [Value Boost] 8 Disciplines Every Decision System Needs · 12 min · Episode 124Machine 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…
- Episode 123: How to Build a Decision Factory Inside Your Organisation · 25 min · Episode 123Data 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…
- Episode 122: [Value Boost] 4 Questions Every Data Scientist Should Ask About AI Strategy · 12 min · Episode 122Choosing 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…
- Episode 121: What Hybrid Agentic AI Organisations Mean for Data Science · 30 min · Episode 121The 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…
- Episode 120: [Value Boost] The AI Silent Correctness Problem · 12 min · Episode 120AI 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…
- Episode 119: Rewiring Your Data Science Thinking for the Agentic AI Era · 29 min · Episode 119The 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…
- Episode 118: [Value Boost] Compounding Your Data Science Authority Beyond Blog Posts · 12 min · Episode 118A 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…
- Episode 117: Writing Your Way to Authority as a Data Scientist · 25 min · Episode 117For 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…
- Episode 116: [Value Boost] What Data Scientists Need to Know Before the AI Free Ride Ends · 14 min · Episode 116Right 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…
- Episode 115: Evolving Your Data Career for the AI Era · 28 min · Episode 115The 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…
- Episode 114: [Value Boost] The Four Conversations Every Data Scientist Needs to Master · 13 min · Episode 114For 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…
- Episode 113: The Experts' AI Manifesto · 27 min · Episode 113Building 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…
- Episode 112: [Value Boost] Lies, Damned Lies and Stakeholders · 16 min · Episode 112AI 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…
- Episode 111: Building Your Defences Against AI Misinformation · 27 min · Episode 111AI 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…
- Episode 110: [Value Boost] Why You Need Less Data Than You Think · 17 min · Episode 110In 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…
