{"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 Reinforcement Learning for Dynamic Pricing","slug":"how-data-scientists-use-reinforcement-learning-for-dynamic-pricing","published_at":"2026-06-15T08:20:53+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-reinforcement-learning-for-dynamic-pricing","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-0052.mp3","audio_url":"https://audio.fexingo.com/business/the-data-science-podcast/episode-0052.mp3","summary":"In this episode of The Data Science Podcast, Lucas and Luna explore how reinforcement learning (RL) is transforming dynamic pricing strategies. Using the example of a major ride-hailing company, they break down how RL algorithms learn to set prices in real time by balancing exploration (testing new price points) and exploitation (using known optimal prices). Lucas explains the core RL concepts of state, action, reward, and the epsilon-greedy algorithm. Luna digs into the practical trade-offs: how often should a model explore versus exploit, and why the reward function must account for long-term customer retention, not just immediate revenue. The conversation also touches on how RL differs from A/B testing in dynamic pricing, the role of simulation environments for training, and ethical considerations around price discrimination. Listeners will walk away with a concrete understanding of RL-based pricing mechanics and a mental model to evaluate pricing algorithms they encounter daily. #ReinforcementLearning #DynamicPricing #DataScience #MachineLearning #RL #PricingStrategy #RideHailing #ExplorationExploitation #EpsilonGreedy #RewardFunction #AIBusiness #Technology #TechPodcast #DataDriven #FexingoBusiness #BusinessPodcast #DataSciencePodcast #Fexingo Keep every episode free: buymeacoffee.com/fexingo","meta_description":"In this episode of The Data Science Podcast, Lucas and Luna explore how reinforcement learning (RL) is transforming dynamic pricing strategies. Using the…","key_points":[],"chapters":[],"topics":[],"duration_seconds":548,"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-reinforcement-learning-for-dynamic-pricing/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-reinforcement-learning-for-dynamic-pricing.md","description":"Read the agent-friendly Markdown representation of this episode resource."}]}}