Value Driven Data Science

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 from dashboard consultant to AI architect [02:35]
2. Why the data team's role is staying the same even as everything around it changes [06:43]
3. How AI is enabling data professionals to build software that used to require a development team [12:11]
4. The best first project to build if you want to develop your AI skills [25:08]
Guest Bio
Nicholas Kelly is the co-founder and Chief AI Architect of Delivering Data Analytics, a consultancy that helps organisations turn data, BI, analytics, and AI into confident decisions people actually act on. He is also the author of Delivering Data Analytics, How to Interpret Data and the recently released The AI-Driven Data Team.
Links
Nicholas's Website
Connect with Nicholas on LinkedIn
Connect with Genevieve on LinkedIn
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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 like a vendor when you're trying to sell expertise [05:09]
Why the value of your work resides in your stakeholder not in you [09:53]
The single question that unlocks what your stakeholder truly values [12:13]
Guest Bio
Blair Enns is the founder of Win Without Pitching, the leading authority on selling and pricing for expert advisors and practitioners. He is also the author of The Win Without Pitching Manifesto and The Four Conversations: a New Model for Selling Expertise, and is the co-host, with David C. Baker, of the podcast 2Bobs: Conversations on the Art of Creative Entrepreneurship.
Links
Connect with Blair on LinkedIn
Blair's website
Connect with Genevieve on LinkedIn
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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 solve  [14:28]
How to decide which skills are worth protecting and which to let go [17:49]
Guest Bio
Blair Enns is the founder of Win Without Pitching, the leading authority on selling and pricing for expert advisors and practitioners. He is also the author of The Win Without Pitching Manifesto and The Four Conversations: a New Model for Selling Expertise, and is the co-host, with David C. Baker, of the podcast 2Bobs: Conversations on the Art of Creative Entrepreneurship.
Links
The Experts' AI Manifesto
Connect with Blair on LinkedIn
Blair's website
Connect with Genevieve on LinkedIn
Be among the first to hear about the release of each new podcast episode by signing up HERE

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 experienced decision makers [01:56]
2. How to arm your stakeholders with the right questions to push back on data [07:57]
3. Why confirmation bias is the most dangerous data vulnerability in any organisation [09:20]
4. What it means when an analytics team is asked to confirm a decision rather than inform one [13:24]
Guest Bio
Derek Gibson is a decision scientist, analytics educator, and has recently wrapped up his long career in financial services at Wells Fargo. He serves on the Wake Forest University MS Business Analytics Advisory Board. He is also a co-author of Data Duped: How to Avoid Being Hoodwinked by Misinformation and author of the upcoming Data, AI, and the Noise: Searching for Truth in Information and Algorithms.
Links
Connect with Derek on LinkedIn
Derek's website
Connect with Genevieve on LinkedIn
Be among the first to hear about the release of each new podcast episode by signing up HERE

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 stakeholders.
In this episode, you'll discover:
Why AI is not a truth tool and what that means for how you use it [03:21]
The red flags that signal an AI output shouldn't be trusted [12:21]
A simple prompting habit you can develop to reduce AI mistakes [16:13]
Why the skill of verifying AI outputs is one you need to build yourself [24:25]
Guest Bio
Derek Gibson is a decision scientist, analytics educator, and has recently wrapped up his long career in financial services at Wells Fargo. He serves on the Wake Forest University MS Business Analytics Advisory Board. He is also a co-author of Data Duped: How to Avoid Being Hoodwinked by Misinformation and author of the upcoming Data, AI, and the Noise: Searching for Truth in Information and Algorithms.
Links
Connect with Derek on LinkedIn
Derek's website
Connect with Genevieve on LinkedIn
Be among the first to hear about the release of each new podcast episode by signing up HERE