Episode 8: From Zero to Scale: Lessons from Airbnb and Beyond

High Signal: Data Science | Career | AI

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This Is Woman's Work with Nicole Kalil

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Grown-Up Goals: The 5 Pillars Of Being A Healthy Adult with Michelle Chalfant | 317 35:24

23 روز پیش35:24

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35:24

Let’s talk about adulting— actual adulting. Not just paying bills or keeping a houseplant alive, but the kind that involves emotional maturity, healthy boundaries, and conscious self-leadership. Because let’s be honest, most of us weren’t taught how to be fully functioning adults… and it shows. Joining us is Michelle Chalfant , licensed therapist turned holistic life coach, creator of The Adult Chair® model, and author of the new book The Adult Chair: Get Unstuck, Claim Your Power, and Transform Your Life . With millions reached through her podcast, coaching programs, and retreats, she’s here to walk us through the five pillars of being a healthy, grounded adult. Here’s the truth: being an adult isn’t about checking boxes or pretending you’re fine. It’s about owning your truth. Feeling your feelings. Practicing compassion without letting yourself off the hook. It’s about setting firm boundaries—with no need for justification—and recognizing that your triggers are not flaws, they’re clues. None of us were handed a guidebook for how to grow up emotionally. We inherited patterns from people who were figuring it out as they went. But what Michelle shares today is empowering: it’s never too late to unlearn what no longer serves you and become the adult you were meant to be. Whether you’re starting this work or knee-deep in your personal development era, this episode will meet you where you are—and help you move forward with clarity, self-trust, and strength. Connect with Michelle: Website: https://theadultchair.com/ Book: https://theadultchair.com/book IG: https://www.instagram.com/themichellechalfant/?hl=en FB: https://www.facebook.com/@TheMichelleChalfant/ YouTube: https://www.youtube.com/c/michellechalfant Related Podcast Episodes: How To Build Emotionally Mature Leaders with Dr. Christie Smith | 272 Boundaries vs. Ultimatums with Jan & Jillian Yuhas | 297 Gentleness: Cultivating Compassion for Yourself and Others with Courtney Carver | 282 Share the Love: If you found this episode insightful, please share it with a friend, tag us on social media, and leave a review on your favorite podcast platform! 🔗 Subscribe & Review: Apple Podcasts | Spotify | Amazon Music Learn more about your ad choices. Visit megaphone.fm/adchoices…

حدود یک سال پیش 1:06:42

MP3•خانه قسمت

In this episode of High Signal, Elena Grewal—former Head of Data Science at Airbnb, political consultant, professor at Yale, and ice cream shop owner—shares her journey of building data teams that scale across vastly different contexts. Drawing on her experiences in tech, consulting, and brick-and-mortar, Elena offers practical lessons on leadership, trust, and experimentation.

Key topics from the conversation include:

From Zero to Scale: How Elena built Airbnb’s data science function from the ground up, scaling it to a 200-person team while driving impact across the organization.
Trust and Team Culture: Why trust is foundational for building effective teams, fostering creativity, and empowering data scientists to drive results.
Applying Data Science Across Contexts: Lessons learned from using data to inform decisions in politics, academia, and even running an ice cream shop.
Experimentation and Iteration: Insights into tailoring experimentation methods to fit different scales, from small businesses to tech giants.
Critical Thinking and Data: How Elena equips the next generation of leaders at Yale to ask better questions, assess data quality, and think critically about evidence.

💡 Tune in to explore how data science principles can scale across industries, the leadership skills required to build impactful teams, and why experimentation is as relevant to ice cream as it is to AI systems.

You can find more on our website: https://high-signal.delphina.ai/

SHOW NOTES

19 قسمت

#Tech #Delphina #Data #Data Science #Machine Learning #Business

Episode 8: From Zero to Scale: Lessons from Airbnb and Beyond

High Signal: Data Science | Career | AI

published حدود یک سال پیش

اشتراک گذاری

MP3•خانه قسمت

Key topics from the conversation include:

From Zero to Scale: How Elena built Airbnb’s data science function from the ground up, scaling it to a 200-person team while driving impact across the organization.
Trust and Team Culture: Why trust is foundational for building effective teams, fostering creativity, and empowering data scientists to drive results.
Applying Data Science Across Contexts: Lessons learned from using data to inform decisions in politics, academia, and even running an ice cream shop.
Experimentation and Iteration: Insights into tailoring experimentation methods to fit different scales, from small businesses to tech giants.
Critical Thinking and Data: How Elena equips the next generation of leaders at Yale to ask better questions, assess data quality, and think critically about evidence.

You can find more on our website: https://high-signal.delphina.ai/

SHOW NOTES

19 قسمت

#Tech #Delphina #Data #Data Science #Machine Learning #Business

همه قسمت ها

High Signal: Data Science | Career | AI

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Episode 19: Defaults, Decisions, and Dynamic Systems: Behavioral Science Meets AI 54:08

۸ hours پیش54:08

54:08

Lis Costa, Chief of Innovation and Partnerships at the Behavioural Insights Team, joins High Signal to explore how behavioral science is reshaping public policy, digital platforms, and machine learning. She explains how defaults influence behavior at scale, why personalization and chatbots are unlocking new kinds of interventions, and what happens when AI systems meet real-world complexity. We also discuss the limits of nudging, the promise of boosting, and why building for human decision-making requires more than just good models. LINKS The Behavioral Insights Team Lis Costa on LinkedIn High Signal podcast Delphina's Newsletter…

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Episode 18: High-Stakes AI Systems and the Cost of Getting It Wrong 58:45

15 روز پیش58:45

58:45

Sudarshan Seshadri—VP of AI, Data Science, and Foundations Engineering at Alto Pharmacy—joins us to explore what it takes to build high-stakes AI systems that people can actually trust. He shares lessons from deploying machine learning and LLMs in healthcare, where speed, safety, and uncertainty must be carefully balanced. We talk about designing AI to support pharmacist judgment, the shift from bottlenecks to decision backbones, and why great data leaders are really architects of how irreversible decisions get made. LINKS Suddu on LinkedIn Careers at Alto Pharmacy High Signal podcast Delphina's Newsletter…

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۵ weeks پیش53:52

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Roberto Medri, VP of Data Science at Instagram, explains why most experiments fail, how misaligned incentives warp product development, and what it takes to drive real impact with data science. He shares what teams get wrong about launches, why ego gets in the way of learning, and how Instagram turned Reels from a struggling product into a global success. A candid look at product, data, and decision-making inside one of the world’s most influential platforms. LINKS Roberto on LinkedIn High Signal podcast Delphina's Newsletter…

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Episode 16: How Human-Centered AI Actually Gets Built 47:22

۷ weeks پیش47:22

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Episode 15: Why Good Metrics Still Lead to Bad Decisions — and How to Fix It 54:17

10 weeks پیش54:17

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Eoin O'Mahony—data science partner at Lightspeed, former Uber science lead, and one of the early architects of the system that kept NYC’s Citi Bikes available across the city—argues that positive metrics are meaningless if you don’t understand the mechanism behind them. At Uber, he was careful to make sure his launches both looked good on paper and made sense in practice. Now in venture, he’s applying that same rigor to unstructured data—using GenAI to scale a kind of work that’s long resisted systematization. LINKS Eoin's page at Lightspeed Ventures Ramesh Johari on How to Build an Experimentation Machine and Where Most Go Wrong Chiara Farronato on Data Science Meets Management: Teamwork, Experimentation, and Decision-Making Delphina's Newsletter…

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12 weeks پیش51:58

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14 weeks پیش1:23:09

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Episode 12: Your Machine Learning Solves The Wrong Problem 54:40

16 weeks پیش54:40

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18 weeks پیش1:05:44

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Episode 10: AI Won't Save You But Data Intelligence Will 59:42

20 weeks پیش59:42

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Episode 9: Why 90% of Data Science Fails—And How to Fix It -- With Eric Colson 1:09:40

22 weeks پیش1:09:40

1:09:40

In this episode of High Signal , Eric Colson—former Chief Algorithms Officer at Stitch Fix and VP of Data Science and Machine Learning at Netflix—breaks down why most companies fail to unlock the full potential of their data science teams. Drawing from years of experience leading data functions at top tech companies, Eric shares how organizations can shift from treating data scientists as a service function to empowering them as strategic drivers of business impact. Key topics from the conversation include: Data Science as a Strategic Function : Why many companies limit their data teams to answering business requests instead of leveraging their ideas for competitive advantage. Beyond Skills—The Power of Cognitive Repertoires : How data scientists' unique ways of framing problems can lead to breakthrough innovations. Trial and Error as a Competitive Advantage : Why most experiments fail—but scaling experimentation is the key to big wins. Decoupling Algorithms from Applications : How separating data science from engineering enables rapid iteration and direct business impact. Shifting from Cost Center to Revenue Generator : Practical steps for structuring data teams to drive measurable value and long-term success. 💡 Tune in to learn how leading companies structure their data teams for impact, why experimentation beats rigid planning, and how treating data science as a strategic function can unlock new business opportunities. You can find more on our website: https://high-signal.delphina.ai/ SHOW NOTES Eric on LinkedIn Beyond Skills: Unlocking the Full Potential of Data Scientists by Eric Colson MultiThreaded: Technology at StitchFix A/B Testing with Fat Tails by Azevedo et al.…

High Signal: Data Science | Career | AI

1
Episode 8: From Zero to Scale: Lessons from Airbnb and Beyond 1:06:42

25 weeks پیش1:06:42

1:06:42

In this episode of High Signal , Elena Grewal—former Head of Data Science at Airbnb, political consultant, professor at Yale, and ice cream shop owner—shares her journey of building data teams that scale across vastly different contexts. Drawing on her experiences in tech, consulting, and brick-and-mortar, Elena offers practical lessons on leadership, trust, and experimentation. Key topics from the conversation include: From Zero to Scale : How Elena built Airbnb’s data science function from the ground up, scaling it to a 200-person team while driving impact across the organization. Trust and Team Culture : Why trust is foundational for building effective teams, fostering creativity, and empowering data scientists to drive results. Applying Data Science Across Contexts : Lessons learned from using data to inform decisions in politics, academia, and even running an ice cream shop. Experimentation and Iteration : Insights into tailoring experimentation methods to fit different scales, from small businesses to tech giants. Critical Thinking and Data : How Elena equips the next generation of leaders at Yale to ask better questions, assess data quality, and think critically about evidence. 💡 Tune in to explore how data science principles can scale across industries, the leadership skills required to build impactful teams, and why experimentation is as relevant to ice cream as it is to AI systems. You can find more on our website: https://high-signal.delphina.ai/ SHOW NOTES Elena's website Elena on LinkedIn Real World Environmental Data Science, Elena's course at Yale Elena's on Orange!…

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Episode 7: What Lies Beyond Machine Learning and AI: Decision Systems and the Future of Data Teams 1:18:44

28 weeks پیش1:18:44

1:18:44

In this episode of High Signal, Chris Wiggins—Chief Data Scientist at The New York Times, Professor at Columbia University, and co-author of How Data Happened—shares how organizations can move beyond prediction to actionable decision systems. Drawing on his work at The New York Times and in academia, Chris explains how to scale data teams, optimize systems, and align data science with organizational impact. Key topics from the conversation include: • From Prediction to Prescription: Why organizations need to focus on interventions that drive outcomes, illustrated with insights like, “Imagine a hospital prescribing treatments instead of just diagnosing conditions.” • The AI Hierarchy of Needs: Foundational practices, such as data logging and engineering, that enable advanced machine learning and AI. • Personalization and Optimization: How reinforcement learning and exploration-exploitation methods help optimize KPIs and adapt to user context. • Scaling Data Teams: Strategies for attracting and retaining talent by emphasizing autonomy, mastery, and purpose. • Empathy as a Data Science Skill: The importance of collaborating with other teams and understanding their goals to drive adoption and success. 🎧 Tune in to learn how to build decision systems, integrate causality into workflows, and develop scalable data science teams for real-world impact. You can find more on our website: https://high-signal.delphina.ai/ LINKS Chris Wiggins' Website Chris Wiggins on LinkedIn How Data Happened: A History from the Age of Reason to the Age of Algorithms The AI Hierarchy of Needs by Monica Rogati The Book of Why by Judea Pearl…

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Episode 6: What Happens to Data Science in the Age of AI? 1:18:23

30 weeks پیش1:18:23

1:18:23

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Episode 5: The Hard Truth About Building AI Systems and What Most Leaders Miss About AI 1:02:06

32 weeks پیش1:02:06

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