{"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":"Why Data Science Projects Fail at the Deployment Stage","slug":"why-data-science-projects-fail-at-the-deployment-stage","published_at":"2026-06-09T20:15:06+00:00","page_url":"https://stenobird.com/podcast/the-data-science-podcast-with-fexingo-analytics-machine-learning-and-data-driven-conversations-7871831/why-data-science-projects-fail-at-the-deployment-stage","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-0041.mp3","audio_url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0041.mp3","summary":"Lucas and Luna tackle the often-overlooked chasm between a promising prototype and a production model that actually drives business value. They dive into a 2023 Gartner finding that 85 percent of data science projects never reach deployment, and unpack the three biggest culprits: misaligned incentives between data scientists and engineers, brittle code that can't scale, and missing infrastructure for monitoring and retraining. Lucas draws on his experience covering MLOps startups to explain why 'it works on my machine' is a design flaw, not a joke. Luna pushes back on the idea that better tools alone solve the problem, arguing that organizational culture and cross-functional communication matter just as much. The episode lands on a concrete framework: start with the deployment environment, build backward, and treat the model as a living system — not a handoff artifact. #DataScience #MLOps #ModelDeployment #DataScienceFailures #Gartner #ProductionML #MachineLearning #Technology #BusinessPodcast #FexingoBusiness #LucasAndLuna #DataPipelines #ModelMonitoring #DataEngineering #CrossFunctionalTeams #DeploymentStrategy #TechTalk #Podcast Keep every episode free: buymeacoffee.com/fexingo","meta_description":"Lucas and Luna tackle the often-overlooked chasm between a promising prototype and a production model that actually drives business value. They dive into…","key_points":[],"chapters":[],"topics":[],"duration_seconds":436,"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/why-data-science-projects-fail-at-the-deployment-stage/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/why-data-science-projects-fail-at-the-deployment-stage.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}