DataScience Show Podcast

Mirko Peters

Welcome to The DataScience Show, hosted by Mirko Peters — your daily source for everything data! Every weekday, Mirko delivers fresh insights into the exciting world of data science, artificial intelligence (AI), machine learning (ML), big data, and advanced analytics. Whether you’re new to the field or an experienced data professional, you’ll get expert interviews, real-world case studies, AI breakthroughs, tech trends, and practical career tips to keep you ahead of the curve. Mirko explores how data is reshaping industries like finance, healthcare, marketing, and technology, providing actionable knowledge you can use right away. Stay updated on the latest tools, methods, and career opportunities in the rapidly growing world of data science. If you’re passionate about data-driven innovation, AI-powered solutions, and unlocking the future of technology, The DataScience Show is your essential daily listen. Subscribe now and join Mirko Peters every weekday as he navigates the data revolution! Keywords: Daily Data Science Podcast, Machine Learning, Artificial Intelligence, Big Data, AI Trends, Data Analytics, Data Careers, Business Intelligence, Tech Podcast, Data Insights. datascience.show Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

  1. Privacy Budget: An Executive Playbook for Managing Data Exposure in Enterprise AI

    13 HR AGO

    Privacy Budget: An Executive Playbook for Managing Data Exposure in Enterprise AI

    Enterprises routinely trade velocity for data exposure without an executive-level ledger to decide what to protect, monitor, or accept. In this 20-minute monologue Mirko introduces the 'Privacy Budget'—a simple, durable governance construct that treats data exposure like a spendable resource. He opens with a concise vignette where untracked customer data access created regulatory callbacks and brand erosion, then presents a non-technical playbook: how to quantify exposure (sensitivity-weighted surface area), set budget caps per product line, risk-rank projects by downstream exposure and business value, and choose mitigations (minimization, masking, synthetic augmentation, contractual limits). Listeners receive board-ready metrics (exposure velocity, budget burn rate, high-risk cohort count), a prioritized 30–90 day checklist to inventory top exposures, and procurement/legal language to bake privacy budgets into vendor contracts. Practical, decision-focused guidance so executives can fund privacy controls where they matter most without halting innovation. CTA: download the Privacy Budget Checklist at datascience.show/privacy-budget. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    9 min
  2. Fairness Debt: An Executive Playbook to Detect, Prioritize, and Remediate Unfair AI

    1 DAY AGO

    Fairness Debt: An Executive Playbook to Detect, Prioritize, and Remediate Unfair AI

    AI systems accrue 'fairness debt'—undetected disparate impacts, buried trade-offs, and shadow remediation costs that compound as models scale. In this 20‑minute executive monologue Mirko opens with a concise vignette where a lending model’s hidden bias produced regulatory scrutiny and a costly remediation program, then lays out a pragmatic, non-technical playbook: rapid detection signals (complaint heatmaps, cohort lift divergence, downstream outcome gaps), a prioritization rubric that converts harms into business and legal exposure, remedial lanes (monitor, reweight, redesign, product exclusion), and funding/contract levers to ensure fixes are timely and measurable. Listeners receive board-ready metrics to report fairness posture, a 30–90 day audit checklist to surface high-impact fairness debt, and negotiation language for procurement and legal to demand remediation SLAs from vendors. Practical and decision-focused for leaders who must reduce harm while preserving strategic momentum. CTA: download the Fairness Debt Audit Toolkit at datascience.show/fairness. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    9 min
  3. Metric Debt: An Executive Playbook to Audit, Align, and Retire Metrics That Break AI

    2 DAYS AGO

    Metric Debt: An Executive Playbook to Audit, Align, and Retire Metrics That Break AI

    Organizations accumulate metric debt: dozens of overlapping KPIs, shifting definitions, and undocumented downstream consumers that cause model drift, perverse incentives, and repeated incidents. In this 20-minute monologue Mirko opens with a concise vignette where competing definitions of “active customer” led models to optimize for the wrong cohort and triggered costly product moves. He then presents a pragmatic, non-technical playbook for leaders: how to inventory high-impact metrics quickly, detect semantic conflicts and hidden consumers, prioritize which metrics to standardize or retire, assign clear ownership and governance, and introduce simple change controls so models and business processes stay aligned. Listeners get board-ready signals to measure metric health (definition divergence, concentration risk, downstream break rate), a prioritized 30–90 day audit checklist, and negotiation language to align product, finance, and data teams. Practical, immediately actionable guidance for executives who must stop metric entropy from eroding AI value. CTA: download the Metric Debt Audit Toolkit at datascience.show/metric-debt. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    12 min
  4. Decision Contracts: Turning Predictions into Accountable Business Actions

    4 DAYS AGO

    Decision Contracts: Turning Predictions into Accountable Business Actions

    Models that emit scores rarely include the binding rules leaders need: who acts, when, at what threshold, and who pays for mistakes. In this 20‑minute executive monologue Mirko introduces ‘Decision Contracts’—compact, board‑readable agreements that translate predictions into executable, funded business decisions. The episode defines the contract’s essential fields (decision trigger and action matrix, costs of false positives/negatives, human‑in‑loop gates, rollback and fallback plans, monitoring SLIs, feedback cadence, funding and escalation clauses), illustrates two anonymized vignettes where absent decision rules caused revenue or compliance harm, and gives a repeatable rubric to draft and pilot Decision Contracts in 30–90 days. Listeners get board‑friendly KPIs, a prioritized checklist to brief legal/procurement/business owners, and a link to download the Decision Contract template to place into procurement and governance cycles. Practical, non‑technical, and immediately actionable for executives who must make predictions produce measurable value. CTA: download the Decision Contract template at datascience.show/decision-contracts. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    10 min
  5. Incentives That Stick: Designing Executive and Team Incentives to Deliver Measurable AI Outcomes

    5 DAYS AGO

    Incentives That Stick: Designing Executive and Team Incentives to Deliver Measurable AI Outcomes

    Too many AI programs fail not for lack of models but because incentives push the wrong behavior: teams optimize vanity metrics, vendors chase one‑time uplift, and business owners avoid ownership of outcomes. In this 20‑minute executive monologue Mirko lays out a compact, pragmatic playbook for designing incentives and performance systems that tie funding, career signals, and product KPIs to measurable business outcomes. The episode explains three incentive levers (funding cadence, metrics architecture, and career/accountability design), gives concrete examples of misaligned incentives and how they produced measurable harm, and presents a repeatable rubric to choose metrics that resist gaming (multi-horizon measures, cohort-based LTV, cost‑to‑serve). Listeners receive a prioritized 30–90 day checklist to audit current incentives, sample KPI translations for finance/product/data, and negotiation language to align procurement and legal. Practical, non‑technical, and immediately actionable for leaders who must turn pilots into sustained value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    11 min
  6. SLOs for AI: An Executive Playbook to Define, Monitor, and Enforce Model & Data Service-Level Objectives

    6 DAYS AGO

    SLOs for AI: An Executive Playbook to Define, Monitor, and Enforce Model & Data Service-Level Objectives

    Executives often demand reliability from AI but lack a shared language to measure it. In this 20-minute monologue Mirko opens with a concise vignette where unseen model latency and stale features caused revenue slippage, then delivers a compact, decision-first playbook for Service-Level Objectives (SLOs) tailored to models and data. Listeners learn how to define business-aligned SLOs (accuracy bands, latency windows, freshness, fairness thresholds), set error budgets, choose a minimal monitoring signal set that executives can read, and map SLO breaches to concrete decision gates and funding actions. Practical artifacts include a board-ready SLO template, example alert thresholds, and a prioritized 30–90 day pilot plan to embed SLOs into governance. The episode keeps trade-offs explicit and non-technical so leaders can commission measurable reliability commitments. CTA: download the Executive SLO Template and 30–90 Day Playbook at datascience.show/slo. That’s the difference between models and value. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    9 min
  7. Price of Intelligence: An Executive Playbook for Governing Algorithmic Pricing

    5 FEB

    Price of Intelligence: An Executive Playbook for Governing Algorithmic Pricing

    Dynamic pricing can unlock margin and responsiveness, but when algorithmic prices misalign with customer expectations or regulation, revenue wins can turn into churn, complaints, and legal risk. In this 20‑minute executive monologue Mirko presents a concise playbook for governing algorithmic pricing: translate pricing goals into board-ready SLOs (price stability, realized uplift, churn elasticity), detect economic and fairness drift, set tolerance bands and automated rollback gates, and convert technical signals into commercial decision rules. The episode opens with a short anonymized vignette where a miscalibrated model produced frequent outlier prices and measurable churn, then walks listeners through a prioritized 30–90 day audit and remediation checklist, contract and procurement clauses to insist on with vendors, and practical metrics to report to the board. Listeners leave with immediate actions and a downloadable one-page Algorithmic Pricing Governance Checklist to brief legal, product, and finance teams. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    10 min
  8. Causal Decisioning: How Leaders Prove AI Drives Value

    4 FEB

    Causal Decisioning: How Leaders Prove AI Drives Value

    Many leaders celebrate accurate models but can’t prove they change outcomes. In this 20‑minute episode Mirko opens with a vivid executive vignette: a personalization pilot that tripled engagement yet didn’t move revenue, and uses that story to frame a compact, non‑technical playbook—what he calls causal decisioning—for proving AI actually drives value. He defines causal decisioning and the term “uplift” (the measured change caused by an intervention) in plain English, explains which minimal experiment designs leaders should demand, and includes a short two‑minute worked example showing a simple uplift calculation and how to read a sample dashboard. Practical rollout patterns, governance and consent checkpoints, and a prioritized 30–90 day checklist are provided. Listeners leave with board‑ready KPI translations and a link to download a Causal Decisioning Toolkit (experiment brief, dashboard template, legal checklist) so they can commission evidence and tie funding to measurable ROI. Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support. I share practical AI leadership notes on LinkedIn — the kind you can forward internally or reuse in executive discussions. Follow Mirko on LinkedIn if you want decision-ready frameworks, not hype.

    10 min
See All (33)

About

Welcome to The DataScience Show, hosted by Mirko Peters — your daily source for everything data! Every weekday, Mirko delivers fresh insights into the exciting world of data science, artificial intelligence (AI), machine learning (ML), big data, and advanced analytics. Whether you’re new to the field or an experienced data professional, you’ll get expert interviews, real-world case studies, AI breakthroughs, tech trends, and practical career tips to keep you ahead of the curve. Mirko explores how data is reshaping industries like finance, healthcare, marketing, and technology, providing actionable knowledge you can use right away. Stay updated on the latest tools, methods, and career opportunities in the rapidly growing world of data science. If you’re passionate about data-driven innovation, AI-powered solutions, and unlocking the future of technology, The DataScience Show is your essential daily listen. Subscribe now and join Mirko Peters every weekday as he navigates the data revolution! Keywords: Daily Data Science Podcast, Machine Learning, Artificial Intelligence, Big Data, AI Trends, Data Analytics, Data Careers, Business Intelligence, Tech Podcast, Data Insights. datascience.show Become a supporter of this podcast: https://www.spreaker.com/podcast/datascience-show-podcast--6817783/support.

Information

  • Creator
    Mirko Peters
  • Years Active
    2025 - 2026
  • Episodes
    33
  • Rating
    Clean
  • Copyright
    © Mirko Peters
  • Show Website
    DataScience Show Podcast