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. Human-in-the-Loop at Enterprise Scale: Building Decision Pipelines Executives Can Trust

    -2 ДН.

    Human-in-the-Loop at Enterprise Scale: Building Decision Pipelines Executives Can Trust

    Many organizations treat AI as a drop-in automation rather than a decision partner. This episode gives C-level leaders a practical, strategic playbook for designing human-in-the-loop (HITL) pipelines that balance speed, accuracy, auditability, and risk. I walk through how to pick the right handoff points between models and people, structure escalation and review workflows, measure combined human+model performance, and align incentives and governance so HITL systems produce reliable business outcomes. You’ll hear concrete examples for finance, operations, and customer experience where HITL moved projects from brittle pilots to repeatable production value. The focus is on executive decision-making: investment trade-offs, organizational ownership, KPIs that matter, and how to operationalize responsibility and explainability. By the end, leaders will have a clear checklist to evaluate current initiatives, reduce failure modes, and scale human+AI decisioning with measurable ROI. Subscribe for more executive playbooks from DataScience.Show. 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 мин.
  2. Shadow AI: An Executive Playbook to Discover, Manage, and Harness Unofficial AI Use

    -3 ДН.

    Shadow AI: An Executive Playbook to Discover, Manage, and Harness Unofficial AI Use

    Many enterprises face a parallel AI economy: employees using external models, browser plugins, automation scripts, and SaaS features outside IT’s visibility. This episode gives C-level leaders a practical, strategic monologue on treating 'Shadow AI' as both a risk and an opportunity. You’ll get a repeatable framework to discover unsanctioned AI, assess business impact and compliance exposure, design lightweight governance that preserves velocity, and create safe channels to productize high-value grassroots solutions. The episode translates technical controls into board-level decision criteria—cost, liability, data exposure, and measurable ROI—and explains how to align incentives, create an internal marketplace for validated tools, and operationalize auditing and incident response. Realistic, executive-focused guidance walks leaders through fast wins and durable practices so Shadow AI becomes a managed source of innovation, not a hidden threat. 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.

    8 мин.
  3. Economics-First ML: A C-Suite Playbook for Cost-Aware Models that Protect Margin

    -4 ДН.

    Economics-First ML: A C-Suite Playbook for Cost-Aware Models that Protect Margin

    Many AI projects optimize predictive metrics but leave out the single largest lever for executives: the true economic consequences of model decisions. This episode is a decision-first monologue for C-level leaders and senior data practitioners that explains how to treat machine learning models as cost-aware business instruments. I lay out a practical playbook to translate strategy into objective functions, quantify asymmetric business costs, design loss functions and sampling strategies that reflect revenue and risk, and operationalize cost-aware SLOs and monitoring. You’ll get concrete governance guardrails, an auditable KPI set to present to boards, a 90-day pilot blueprint to validate economics in production, and real trade-offs of complexity versus clarity. The focus is executable guidance—how to fund, measure, and hold teams accountable so ML becomes a predictable contributor to margin and not an opaque technical bet. 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 мин.
  4. Feature as Product: A C-Suite Playbook for Reusable ML Assets

    -6 ДН.

    Feature as Product: A C-Suite Playbook for Reusable ML Assets

    Enterprises routinely waste time and budget reengineering the same features across teams, leaving ML delivery slow, costly, and non-repeatable. This episode gives C-level leaders and senior data executives a concrete playbook to treat features as products: define ownership, funding models, SLAs, a searchable feature catalog, and lifecycle gating so feature work becomes auditable and fundable. Mirko walks through product-style RACI, a pragmatic funding taxonomy (central product funding vs. internal chargebacks), example KPIs (feature reuse rate, cost-per-feature, time-to-production, ROI-per-feature), and a 90-day pilot checklist to prove value quickly. Listeners get practical trade-offs—centralize vs. federate, observable lineage to business metrics, and controls to avoid hidden technical debt. The episode is tactical, executive-focused, and designed to convert pilots into sustained capability with measurable outcomes for the board. 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 мин.
  5. ML Chaos Playbook: A C-Suite Guide to Testing, Observability, and Recovery

    16 АПР.

    ML Chaos Playbook: A C-Suite Guide to Testing, Observability, and Recovery

    Many enterprise AI failures trace to untested assumptions at the intersection of models, data flows, and product behaviour. In this 23-minute, decision-first monologue Mirko synthesizes lessons from senior CDOs and ML leaders into a compact, fundable playbook for operational resilience. Executives receive explicit artifacts they can take to the board: two sample SLOs (decision-level error cost and model MTTx targets), a template rollback criteria checklist, a one-paragraph runbook snippet, and a 90-day pilot plan with clear success metrics and cost estimates. Mirko clearly signals when advice is a composite of real-world examples versus prescriptive guidance, and walks through how to scope low-blast experiments, budget resilience as an auditable initiative, align ownership and procurement, and report risk reduction with board-ready KPIs. Practical, non-technical, and governance-aware, this episode helps leaders fund resilience so AI delivers measurable business outcomes under real-world stress. 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 мин.
  6. Data Contracts as a Funded Service: A Board‑Ready SLA Template and 90‑Day Pilot for Reliable Data

    14 АПР.

    Data Contracts as a Funded Service: A Board‑Ready SLA Template and 90‑Day Pilot for Reliable Data

    Enterprises repeatedly lose time and value to brittle data handoffs: unknown ownership, unpredictable quality, and project delays. This monologue gives executives a decision‑first playbook to institutionalize 'Data Contracts as a Service.' Mirko lays out a concise, board‑ready SLA template (availability, freshness, lineage, MTTR, change notifications), a pragmatic costing model for funding producer teams, and a 90‑day pilot plan that converts upstream work into measurable outcomes. Listeners will get concrete KPIs to present to boards (data availability %, mean time to detect/fix failures, cost-per-feature, business value per feed), stakeholder engagement tactics (RACI, negotiation script, incentive levers), and a phased rollout that prevents bureaucracy. The episode balances tradeoffs—centralized guardrails vs. federated ownership, tight SLAs vs. innovation velocity—and finishes with two immediate executive actions to de‑risk feeds that matter most. 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 мин.
  7. Synthetic Data Governance: An Executive Playbook to Certify, Procure & Trust Synthetic Training Data

    12 АПР.

    Synthetic Data Governance: An Executive Playbook to Certify, Procure & Trust Synthetic Training Data

    Synthetic data is rapidly becoming a core input for training, testing, and privacy-preserving sharing—but it brings unique governance, provenance, and legal trade-offs that boards must fund and control. This non‑technical, executive‑grade monologue opens with two crisp vignettes: a synthetic augmentation that amplified bias in a high-value cohort, and a synthetic test set that masked a downstream production failure. Mirko then delivers a pragmatic playbook: a certification rubric (fidelity, representativeness, privacy leakage, lineage), minimal evidence packs to demand from teams and vendors, conservative heuristics to dollarize synthetic risk vs value, procurement clauses for attestations and sample‑escrow, and a 30–90 day pilot to certify one synthetic pipeline. Listeners leave with board‑read KPIs (synthetic‑coverage %, privacy-leakage score, model‑delta after synthetic augmentation), three immediate executive moves, and a clear subscribe CTA to access a one‑page Synthetic Data Checklist. 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 мин.
  8. Uncertainty Accounting: A C‑Suite Playbook to Measure, Budget & Hedge Model Overconfidence

    9 АПР.

    Uncertainty Accounting: A C‑Suite Playbook to Measure, Budget & Hedge Model Overconfidence

    Models don't just make mistakes—they can be confidently wrong. This non‑technical, executive‑grade monologue shows leaders how to turn abstract uncertainty into board‑read controls: a taxonomy of uncertainty (aleatoric, epistemic, distributional shift), minimal evidence packs to demand (calibration curves, prediction intervals, decision‑aware confidence histograms), pragmatic methods to dollarize overconfidence exposure, and a short menu of hedges (conservative defaults, staged funding reserves, human‑review corridors, insurance triggers). Mirko opens with two crisp vignettes—a loan decline with misplaced confidence and a recommender that confidently amplified churn—then outlines governance, procurement language to require uncertainty hooks from vendors, and a 30–90 day pilot to instrument one critical flow. Leaders leave with board KPIs (calibration gap, uncertainty burn rate, hedge coverage %) and three immediate moves. Subscribe to DataScience.Show to turn uncertainty into auditable capital. 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 мин.
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Об этом подкасте

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.

Информация

  • Автор
    Mirko Peters
  • Годы выхода
    2025 - 2026
  • Выпуски
    64
  • Ограничения
    Без ненормативной лексики
  • Авторские права
    © Mirko Peters
  • Сайт подкаста
    DataScience Show Podcast