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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,…
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…
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,…
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…
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…
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…
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…
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…
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…
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…
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…
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…
Episode 97: [Value Boost] Mathematical Modelling as a Gateway to ML Success
Data scientists often jump straight to machine learning when tackling a new problem. But there's a foundational step that can dramatically increase your chances of project success and create more…
Episode 96: Making Better Decisions with ML and Optimisation
Data scientists use optimisation every day when training machine learning models, without even thinking about it. But there's another type of optimisation - that many data scientists are unaware of -…
Episode 95: [Value Boost] Building Models That Work While Millions Are Watching
Building a model for an academic paper is one thing. Building a model that has to work perfectly during the Cricket World Cup with millions watching is something else entirely. There's no room for…
Episode 94: Creating Global Impact with Data Science
For most data scientists, the idea of impacting the world through your work seems impossible. You may be developing technically brilliant solutions within your organisation, but seeing them become…
Episode 93: [Value Boost] What Industry Data Scientists Can Learn from Academic Training
While the transition from academia to industry can be brutal for data scientists, academics don't show up in industry empty-handed. They bring powerful transferable skills that many industry-trained…
Episode 92: Making the Academia to Industry Leap in Data Science
Making the leap from academia to industry isn't just another career change - it involves a complete shift in the way you work. Data scientists transitioning from academia face a brutal learning curve…
Episode 91: [Value Boost] How Your Hobbies Can Supercharge Your Data Science Career
Activities outside of data science can strengthen the very skills data scientists need for their careers in surprising ways. From improving stakeholder communication to learning how to work with…
Episode 90: Using LLMs to Become a More Effective Data Scientist
When most data scientists think about using LLMs and generative AI, the first thing that springs to mind is writing code faster. While that's certainly useful, if it's the only application you're…
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Value Driven Data Science has published 109 episodes since September 2022, covering topics in Business, Technology.
Value Driven Data Science is currently highly active with new episodes weekly. Average episode length is 36m.
