{"podcast":{"title":"The Data Science Podcast with Fexingo: Analytics, Machine Learning, and Data-Driven Conversations","slug":"the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831","podcast_index_feed_id":7871831,"rss_url":"https://feeds.fexingo.com/business/the-data-science-podcast.xml","website_url":"https://www.fexingo.com/","image_url":"https://audio.fexingo.com/business/the-data-science-podcast/cover.png","author":"Fexingo","episode_count":118,"summary":"Lucas and Luna sit at a data-science workstation, two thin laptops open to scatter plots and clustering visualizations, and ask: what can we actually learn from the numbers? Each episode of The Data Science Podcast with Fexingo is a grounded, specific conversation about a single analytics problem or machine-learning method — from regularization in regression to the bias-variance trade-off in random forests. Lucas leads with a journalistic eye for how models are built and tested in the real world, citing actual case studies like how Netflix used matrix factorization for recommendations or how healthcare researchers apply survival analysis to clinical trials. Luna keeps the discussion honest, asking about data quality, feature engineering pitfalls, and whether a model’s accuracy actually translates to business value. They never resort to buzzwords: instead, they walk through the workflow from data collection to deployment, discussing trade-offs like interpretability versus performance. The show serves data scientists, analysts, and engineers who want to stay sharp on methods without the hype. Listeners walk away with a clearer understanding of why one algorithm beats another on a gi…","last_synced_at":"2026-07-19T08:17:23.323447+00:00","page_url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831"},"episode":{"title":"How Data Scientists Use Monte Carlo Simulations for Risk","slug":"how-data-scientists-use-monte-carlo-simulations-for-risk","published_at":"2026-07-11T08:34:52+00:00","page_url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-monte-carlo-simulations-for-risk","show_page_url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831","url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0103.mp3","audio_url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0103.mp3","summary":"Episode 103 of The Data Science Podcast with Fexingo. Lucas and Luna dive into Monte Carlo simulations — not as a textbook concept, but as a practical tool data scientists use to quantify uncertainty. They walk through a real-world case: a mid-size logistics company that used Monte Carlo to model delivery times under variable traffic, weather, and fuel costs. Lucas explains the math behind random sampling, how to choose the number of simulations, and the common pitfall of assuming normal distributions. Luna challenges him on interpretability — how do you explain a distribution of outcomes to a non-technical stakeholder? They also discuss modern libraries like NumPy and PyMC, and how cloud computing has made millions of simulations feasible on a laptop. No abstract theory — just a grounded look at when Monte Carlo beats deterministic models and when it doesn't. By the end, you'll know exactly how to frame a Monte Carlo problem for your next data science project. #MonteCarlo #RiskSimulation #DataScience #UncertaintyQuantification #NumPy #PyMC #Logistics #PredictiveModeling #Simulation #BusinessAnalytics #MachineLearning #Probability #DecisionMaking #StochasticModeling #Technology #FexingoBusiness #BusinessPodcast #DataDriven Keep every episode free: buymeacoffee.com/fexingo","meta_description":"Episode 103 of The Data Science Podcast with Fexingo. Lucas and Luna dive into Monte Carlo simulations — not as a textbook concept, but as a practical too…","key_points":[],"chapters":[],"topics":[],"duration_seconds":531,"processing_state":"not_requested","actions":[{"name":"request_transcript","method":"POST","url":"https://stenobird.com/v1/public/podcasts/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/episodes/how-data-scientists-use-monte-carlo-simulations-for-risk/transcription-requests","description":"Idempotently request low-priority transcript generation for this episode."},{"name":"read_markdown","method":"GET","url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/how-data-scientists-use-monte-carlo-simulations-for-risk.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}