Episode 70: How to Interpret Data Like a Pro in the Age of AI
Despite unprecedented data abundance and widespread data science education, even experienced data professionals still struggle to interpret data effectively. They draw wrong conclusions, miss critical insights, or fail to communicate findings in actionable ways.In this episode, Nicholas Kelly joins Dr. Genevieve Hayes to tackle the critical challenge of data interpretation - revealing why technical expertise alone isn't enough and sharing practical frameworks for transforming raw data into actionable business insights that drive real organisational change.This conversation reveals:The four primary challenges that make data interpretation so difficult [02:24]Why ChatGPT and AI tools are changing the data interpretation landscape [06:23]The "Five Whys" technique that ensures you're asking the right questions instead of wasting time on problems everyone already understands [17:32]Why successful data projects don't end with presenting insights and what to do next [20:01]Guest BioNicholas Kelly is the founder of Delivering Data Analytics, a consultancy focused on helping organisations enable their teams to make smarter, faster, and more confident decisions through data and AI. He is also the author of Delivering Data Analytics and the recently released How to Interpret Data.LinksNicholas's WebsiteConnect with Nicholas on LinkedInConnect 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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Episode 69: [Value Boost] The Value Proposition Framework Every Data Scientist Needs to Master
Can you clearly articulate what makes your data science work valuable - both to yourself and to your key stakeholders? Without this clarity, you'll struggle to stay focused and convince others of your worth.In this Value Boost episode, Dr. Peter Prevos joins Dr. Genevieve Hayes to share how creating a compelling value proposition transformed his data team from report writers to strategic partners by providing both external credibility and internal direction.This episode reveals:Why a clear purpose statement serves as both an external marketing tool and an internal compass for daily decision-making [02:09]A framework for identifying your stakeholders' true pain points and how your data skills can address them [04:48]A practical first step to develop your own value statement that aligns with organizational strategy while focusing your daily work [06:53]Guest BioDr Peter Prevos is a water engineer and manages the data science function at a water utility in regional Victoria. He runs leading courses in data science for water professionals, holds an MBA and a PhD in business, and is the author of numerous books about data science and magic.LinksConnect with Peter on LinkedInA Brief Guide to Providing Insights as a Service (IaaS)Connect 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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Episode 68: How to Market Your Data Science Skills Internally with the Insights-as-a-Service Approach
Internal data science teams face a unique challenge - they're providing an invisible service that only gets noticed when something goes wrong. This puts data scientists in the awkward position of having to market themselves within their own organization, without any marketing training.In this episode, Dr. Peter Prevos joins Dr. Genevieve Hayes to share how he applied his PhD research in services marketing to transform his water utility's data team from "report writers" to strategic partners by positioning data science as "Insights-as-a-Service."This episode explains:Why treating data science as "Customer Satisfaction Engineering" rather than technical implementation shifts everything about team effectiveness [08:19]How understanding both the financial and psychological "price" users pay for insights leads to dramatically better adoption [14:36]The treasure hunt technique that transformed how stakeholders discover and engage with available data resources [18:17]Why the mantra "99% of business problems don't need machine learning" can paradoxically increase your data science impact [22:29]Guest BioDr Peter Prevos is a water engineer and manages the data science function at a water utility in regional Victoria. He runs leading courses in data science for water professionals, holds an MBA and a PhD in business, and is the author of numerous books about data science and magic.LinksConnect with Peter on LinkedInA Brief Guide to Providing Insights as a Service (IaaS)Connect 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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Episode 67: [Value Boost] The 3 Level Hierarchy That Protects Your Data Science Credibility
When deadlines loom, it's easy for data scientists to fall into the trap of cutting corners and bending analyses to deliver what stakeholders want. But what if a simple framework could help you maintain quality under pressure while preserving your professional integrity?In this Value Boost episode, Dr. Brian Godsey joins Dr. Genevieve Hayes to reveal his powerful "Knowledge first, Technology second, Opinions third" hierarchy - a framework that will transform how you handle stakeholder pressure without compromising your standards.In this episode, you'll discover:Why this critical hierarchy gets dangerously inverted when deadlines loom and how to prevent it from undermining your credibility [01:05]How to resist the career-limiting trap of cherry-picking facts that merely support executive opinions [04:09]A practical note-taking technique that keeps you anchored to reality when stakeholders push for convenient answers [06:04]The one transformative habit that separates truly valuable data scientists from those who merely validate existing assumptions [07:17]Guest BioDr Brian Godsey is a Data Science Lead at AI platform as a service company DataStax. He is also the author of Think Like a Data Scientist and holds a PhD in Mathematical Statistics and Probability.LinksBrian's websiteConnect with Brian on LinkedInConnect 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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Episode 66: How to Think Like a Data Scientist (Even While AI Does All the Work)
The data science world has always been obsessed with tools and techniques - a fixation that's only intensified in the era of generative AI. Yet even as ChatGPT and similar technologies transform the landscape, the fundamental challenge remains the same - turning technical capabilities into business results requires a process most data scientists never learned.In this episode, Dr. Brian Godsey joins Dr. Genevieve Hayes to discuss why the scientific process behind data science remains more critical than ever, sharing how his original "Think Like a Data Scientist" framework has evolved to harness today's powerful AI capabilities while maintaining the principles that drive real business values.This conversation reveals:Why the seemingly basic question "Where do I start?" continues to derail data scientists' effectiveness and how mastering the right process can transform your impact [01:15]The three stages of the data science process that remain essential for career success even as AI dramatically changes how quickly you can execute them [11:07]How the accessibility revolution of generative AI creates new career opportunities for data scientists in organizations that previously couldn't leverage advanced analytics [18:34]The underrated troubleshooting skill that will make you invaluable as organizations increasingly rely on "black box" AI models for business-critical decisions [20:21]Guest BioDr Brian Godsey is a Data Science Lead at AI platform as a service company DataStax. He is also the author of Think Like a Data Scientist and holds a PhD in Mathematical Statistics and Probability.LinksBrian's websiteConnect with Brian on LinkedInConnect with Genevieve on LinkedInBe among the first to hear about the release of each new podcast episode by signing up HERE
About Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm.
Are you tired of spending hours mastering the latest data science techniques, only to struggle translating your brilliant models into brilliant paychecks?
It’s time to debug your career with Value Driven Data Science. This isn’t your average tech podcast – it’s a weekly masterclass on turning data skills into serious clout, cash and career freedom.
Each episode, your host Dr Genevieve Hayes chats with data pros who offer no-nonsense advice on:
• Creating data solutions that bosses can’t ignore;
• Bridging the gap between data geeks and decision-makers;
• Charting your own course in the data science world;
• Becoming the go-to data expert everyone wants to work with; and
• Transforming from data scientist to successful datapreneur.
Whether you’re eyeing the corner office or sketching out your data venture on your lunch break, Value Driven Data Science is here to help you rewrite your career algorithm.
From algorithms to autonomy - it's time to drive your value in data science.
Listen to Value Driven Data Science: Boost your impact. Earn what you’re worth. Rewrite your career algorithm., Unhedged and many other podcasts from around the world with the radio.net app
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