AI isn't just accelerating productivity, it's reshaping how we structure power, make decisions, and define what "value" means in our organizations.

In this episode, Felicia Newhouse — a data leader, AI strategist, and advocate for ethical, human-centered innovation — brings deep insight into how power structures in business are being reimagined in the age of AI.

We dive into why so-called soft skills like communication, critical thinking, and emotional intelligence are becoming core differentiators in data and AI teams.

With research showing that companies deploying AI without leadership transformation risk ethical blind spots and cultural misalignment, we ask: What kind of leaders do we need now? And how can data professionals step into that shift?

• Why soft skills are no longer optional in data and AI roles

• How leadership, ethics, and communication shape responsible AI outcomes

• Real-world examples of companies gaining trust and performance by elevating human-centered skills

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If you're thinking about Data Analyst or Data Scientist career paths, then this one is for you!

In this episode with Data Career Jumpstart Founder Avery Smith, you'll learn about the differences between Analyst and Data Scientist career paths, and hear some practical advice to help you on your journey.

You'll leave with a better understanding of different data roles, which might be the better fit for you, and a concrete roadmap for taking action and accelerating your career.

• Key differences between Data Analyst and Data Science roles

• The critical tools to focus on to land a job in either role

• A step by step playbook for building the skills you need to succeed

This session was part of our OPEN CAMPUS week in October, which included 6 days of live expert sessions.

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From launching AI products to modernizing legacy data stacks, we're going behind the scenes of data-driven transformation in financial remittance.

In this episode, we sit down with Sia Zahedi, former CDO at a global financial remittance company, to get a candid look at the projects, challenges, and decisions that define data leadership in finance.

If you've ever wondered what it's like to lead data strategy at a global financial company, this one is for you.

• What the day-to-day of a CDO looks like

• Real-world use cases for AI in financial services

• The difference between launching AI prototypes and real products

• Career advice for aspiring CDOs and senior data leaders

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Ken Jee has spent a decade in sports analytics, working at the intersection of data science and athlete performance.

Now, he's building The Exponential Athlete, a podcast dedicated to exploring what makes athletes reach their highest potential.

• His 10-year journey in sports analytics and the lessons data can, and can't teach us about performance.

• How his background in data science set him up to successfully launch The Exponential Athlete.

• The limits of analytics — why diagnosis is easy, but decision-making is complex.

• How mental visualization (seeing success before it happens) plays a crucial role in athletic and personal excellence.

• The intersection of training philosophy, psychology, and data in shaping elite performers.

Whether you're passionate about sports, data science, entrepreneurship, or personal growth, this episode offers practical insights you can apply immediately.

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Too many dashboards. Endless ad-hoc questions.

Analytics teams often get trapped supporting the business, without driving it forward. In this show, Ollie Hughes, CEO of Count, will show you how to break free.

Based on real-world case studies and hard-won experience, Ollie will walk us through:

• The common traps analytics teams fall into — and why good intentions often lead to low impact

• How to shift from "answering questions" to "solving business problems"

• Why operational clarity, not just better data, is the key to better outcomes.

• Real use cases and strategies for building high-leverage analytics inside your organization.

If you're ready to move beyond dashboards and truly drive business success, this is the show you can't afford to miss.

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In this episode, we're joined by Maven's own Chris Bruehl to unpack the 2025 data science landscape and explore what it really takes to break into the field today.

If you're curious about what data scientists actually do — and how to become one — you won't want to miss this!

• How the data scientist role compares to other data careers

• The essential skills you need to land a data science job in 2025

• Smart strategies to position yourself before applying

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LLMs seem like a hot solution now, until you try deploying one.

In this episode, Andriy Burkov, machine learning expert and author of The Hundred-Page Machine Learning Book, joins us for a grounded, sometimes blunt conversation about why many LLM applications fail.

We talk about sentiment analysis, difficulty with taxonomy, agents getting tripped up on formatting, and why MCP might not solve your problems.

If you're tired of the hype and want to understand the real state of applied LLMs, this episode delivers.

• What is often misunderstood about LLMs

• The reliability of sentiment analysis

• How can we make agents more resilient?

📚 Check out Andriy's books on machine learning and LLMs:

The Hundred-Page Machine Learning Book

The Hundred-Page Language Models Book: hands-on with Pytorch

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In this episode, we sit down with Joe Dery, Vice President of Customer Success at Aera Technology, to explore a concept that's shifting how organizations think about analytics: Decision Intelligence.

We unpack what decision intelligence really means (hint: it's not just another buzzword), why some data scientists still resist it, and how this discipline helps surface causal insights — not just correlations. Joe brings firsthand use cases from the field, showing how DI is helping organizations not only analyze what's happening but also decide what to do about it.

Whether you're a data scientist, product manager, or exec who wants to move from dashboards to decisions, this one's for you.

• What decision intelligence is — and what it isn't

• Why some in the data space push back against it

• How DI gets you closer to causality (not just correlation)

• Real-world use cases where DI created business impact

• Why decision metadata is the secret sauce for long-term success

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AI is moving fast, but are organizations prepared to keep up?

In this episode, data professional Laura Madsen joins us to unpack why most companies are lagging behind, how tech debt is holding businesses back, and why knowledge graphs are the way forward.

Join us for a bold conversation on why the AI revolution needs better data governance, not just bigger models.

• Who's thriving in disruption, which industries embrace AI, and why others are stuck

• The hidden cost of tech debt and why most organizations avoid real transformation

• The power of knowledge graphs, and why they're the key to making AI work at scale

• What AI still can't do for us, and the gaps we need to fill with human expertise

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We live in a world where people are concerned about social media tracking their data—but at the same time, willingly send their DNA to companies like 23andMe.

Why does this happen? What do companies actually do with our data? And how can we, as individuals, become more data-literate to make informed decisions?

In this episode, we sit down with Kathy Rondon, author of "We The People: A Playbook for Data Ethics in a Democratic Society," data expert and advocate for data literacy.

If you've ever wondered how to take control of your digital footprint, make sense of statistics, or separate fact from fiction in a world full of data, this episode is for you.

• How companies collect and use your data—sometimes in ways you wouldn't expect

• Why do we trust some organizations with our most personal data while fearing others

• The power of statistics and how understanding the basics would help everyone better navigate news, research, and even politics

📚 Be sure to check out Kathy's book: "We The People: A Playbook for Data Ethics in a Democratic Society"

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