What happens when AI becomes your coworker, not your replacement?

In this episode, we sit down with Sadie St. Lawrence, founder of HMCI, to explore the rapidly evolving future of work, where AI isn't just a tool, but a teammate.

We dig into how blue-collar and white-collar jobs will be shifting as AI and automation move from the periphery into our daily workflows. From analysts to factory floors, from dashboards to shop floors, what will it actually feel like to work alongside intelligent machines?

Sadie also shares the deeply personal story of her 18-month journey exiting Women in Data, what she learned in building a global community, and how she’s now thinking about the next wave of human + AI collaboration.

If you're wondering what your job will look like in 5 years, this one's for you.

• What it really means to work with AI as a teammate

• How analysts can stay relevant in the age of automation

• The different futures ahead for blue- vs. white-collar roles

• How Sadie built, scaled, and thoughtfully exited Women in Data

• What makes a career resilient in an AI-driven economy

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As AI agents become more powerful and widely adopted, enterprises face a new challenge: how to build them on a foundation of trustworthy, AI-ready data that includes both structured and unstructured data.

Unstructured data introduces new complexity for organizations already contending with large and growing volumes of data that is often distributed and disconnected, and from more information sources.

In this episode, Stephanie Valarezo, Program Director, Product, from IBM Data Integration, shares how organizations can simplify and scale the integration, access and governance of unstructured and structured data.

Explore how IBM is simplifying the enterprise data stack by empowering teams to integrate structured and unstructured data, using batch, real-time streaming, or replication techniques, while extending governance beyond the data layer to the AI agents themselves.

Whether you're modernizing legacy infrastructure, accelerating agent development, or building robust governance strategies, this session will give you a blueprint to:

• Unlock the value of unstructured data for enterprise-grade AI
• Accelerate data intelligence through built-in observability and governance
• Simplify your tech stack while improving trust and traceability in AI outputs

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The analytics industry is evolving faster than ever, and staying ahead requires more than technical expertise—it takes community building, internal advocacy, and the ability to drive impactful projects.

In this episode, Dustin Schimek, Data Fluency Program Manager at MedStar Health, discusses the state of analytics in 2025.

We explore what analysts are working on today, the importance of internal evangelism, and how to spearhead new projects and get to proof of concept (POC) quickly. Dustin also shares insights on standout traits for analysts and why community is at the heart of analytics success.

If you’re looking to thrive in analytics and stay at the forefront of the industry, this show is for you!

• Key trends shaping the analytics industry in 2025

• The role of community building and internal evangelism in driving analytics success

• How to accelerate proof of concept (POC) for new analytics projects

• Common themes that make analysts stand out in today’s industry

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Data professionals often excel at technical skills but struggle to connect their work to broader business goals.

In this show, we’re joined by Jordan Morrow, Senior VP of Data and AI Transformation at AgileOne and author of Business 101 for the Data Professional, to discuss bridging the gap between data and strategy.

Jordan offers practical advice on developing business acumen, aligning data work with organizational goals, and communicating effectively with stakeholders.

Whether you’re a data scientist, analyst, or aspiring leader, this conversation will help you unlock the full potential of your data career.

• The essential business skills every data professional needs

• How to align data projects with organizational goals

• Strategies for effective communication with non-technical stakeholders

• Common pitfalls data professionals face when navigating business challenges—and how to avoid them

• Actionable tips to become a more strategic, business-savvy data professional

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What happens when a passion for data science meets the fast-paced world of stock trading?

In this episode, we’re joined by Matt Dancho, Founder of Business Science, Quant Science, and the creator of the popular tidyquant package, who shares his journey from data scientist to launching Business Science and the projects and packages he’s built along the way.

We explore how he leverages Python and R to trade stocks, as well as the lessons he’s learned from building a business in the data.

Whether you’re a data professional, a stock market enthusiast, or an aspiring entrepreneur, this episode is packed with actionable insights to level up your skills and strategies.

• Taking your data skills and furthering your career to make money.

• Tips for working with stock data.

• How AI is changing analytics

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In business, ideas don’t stand alone; they have to be communicated effectively to drive action. Whether through reports, presentations, or product pitches, success comes from not just having data expertise but knowing how to make it matter.

Yet many in the data world focus on just establishing a “personal brand” rather than developing something tangible. So, what does it take to turn expertise into a real product?

In this episode with Scott Taylor, The Data Whisperer, we take a behind-the-scenes look at how creativity and communication shape success in the data space beyond just technical skills or personal branding.

Listen for a raw and insightful conversation on navigating creativity, career growth, and the business of turning data expertise into something real.

• Why communication is a superpower in business and data

• The balance between technical skills and storytelling in shaping ideas

• How creativity applies in a structured B2B context

• Content, branding, and the tools of a data creator—beyond just a LinkedIn presence 

• The challenge of crafting the perfect one-sentence pitch

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Breaking away from the corporate ladder to carve your own path is a journey filled with challenges, growth, and unexpected rewards.

In this episode, we host Christina Stathopoulos: a trailblazer who transitioned from a Google role to entrepreneurship and gained experience trying to build her own company in Spain! 

Together, we explore what it means to make an impact in your career, the art of building a personal brand, and how to navigate pivotal career decisions with confidence.

Christina shares candid advice and discusses how embracing change can lead to unparalleled opportunities but also can lead to difficulties.

Whether you’re dreaming of stepping into entrepreneurship, striving to shape a meaningful career, or looking to grow your personal brand, this show will be packed with insights for data professionals!

• Actionable advice for shaping a career aligned with your goals and values.

• How to transition from corporate to entrepreneurship.

• The importance of building a personal brand and why it matters.

• Insights from working abroad: perspectives on career and growth.

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Data science isn’t just about models and code—it’s about people, connections, and shared knowledge.

From online forums to in-person hackathons, communities play a crucial role in shaping careers and innovations. In this episode, we’re joined by Yujian Tang — an expert in building and fostering data-driven communities — to discuss how these spaces can help you grow and why developer advocacy is a great role for people passionate about both building and fostering community.

Whether you're looking to expand your network, break into data science, or grow your own community, this episode is packed with actionable insights from someone who has done it all.

• How getting involved in different communities can accelerate your career and open up unexpected opportunities

• The key differences between various data communities and how to find the right fit

• What it takes to build and nurture a thriving community of your own

• The evolving role of the Developer Advocate in growing data product visibility through community.

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Agentic AI is here, but what is it? What are the differences between the traditional LLMs and this new agentic AI we’re hearing about? With AI systems making autonomous decisions, driving analytics, and reshaping data strategies, what does this mean for analysts?

We’re joined by Vin Vashishta, CEO at V Squared and an expert in AI strategy and data science. Vin’s book, From Data to Profit, lays out a roadmap for turning AI and analytics into real business value. 

AI isn’t just a tool anymore; it’s becoming a collaborator. How should we think about adapting? Don’t miss his insights in this show!

• How Agentic AI will redefine the role of analysts in analytics.

• What makes an AI ‘agent’ different from a traditional LLM?

• Why knowledge graphs are the key to AI’s next leap forward.

• How to future-proof your career in analytics.

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Are you ready to level up your analytics game and tackle the challenges that come with data-heavy projects?

In this episode, Harpreet Sahota, a data science leader with years of experience helping analysts and teams thrive, shares actionable insights and strategies for staying ahead in the fast-evolving world of data.

Harpreet will help you develop a practical mindset to tackle real-world challenges and build the confidence to lead impactful projects. From cleaning messy datasets, to deciding between building or buying a solution, to training a computer vision model, Harpreet is here to share his expertise.

Whether you’re an aspiring data analyst or a seasoned professional, this episode will equip you with the skills and clarity to succeed.

• Data Cleaning for Any Data Type: Proven techniques to clean and prepare your data for analysis.

• Training a Computer Vision Model: What to consider before you start and how to ensure success.

• Build vs. Buy for LLMs: When to create your own solution and when to leverage existing tools.

• Setting Yourself Up for Success as an Analyst: Strategies to stand out and make your work impactful.

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Interested in learning more from Harpreet? Connect with him on LinkedIn

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