script for meta descriptions and updated pages

kavaivaleri · kavaivaleri · commit 98e831403754 · 2025-11-07T14:10:04.000+01:00
diff --git a/_podcast/s03e04-interviewing-300-data-scientists.md b/_podcast/s03e04-interviewing-300-data-scientists.md
@@ -1,7 +1,8 @@
 ---
 title: 'Data Science Interview Guide: CV Optimization, Take-Home Projects, Mock Interviews
   & Negotiation'
-short: 'Data Science Interview Guide: CV Optimization, Take-Home Projects, Mock Interviews & Negotiation'
+short: 'Data Science Interview Guide: CV Optimization, Take-Home Projects, Mock Interviews
+  & Negotiation'
 guests:
 - olegnovikov
 image: images/podcast/s03e04-interviewing-300-data-scientists.jpg
@@ -918,23 +919,27 @@ transcript:
   sec: 4194
   time: '1:09:54'
   who: Alexey
-intro: "How do you make your data science application stand out, ace take-home projects,
+intro: How do you make your data science application stand out, ace take-home projects,
   and negotiate an offer without leaving money on the table? In this episode, Oleg
   Novikov — creator of NextRound and former data science manager at Uber with a background
   in data and software engineering — walks through a practical data science interview
   guide covering CV optimization, take-home projects, mock interviews, and negotiation.
   <br><br> We dig into career trajectory from engineering to product data science,
   building projects that differentiate your application, and concrete product work
-  like forecasting and LTV. Oleg demonstrates NextRound's mock-interview chatbot and personalized
-  feedback, explains common hiring funnels (recruiter screen → take-home → interviews),
-  and contrasts product data scientist vs. machine learning engineer expectations.
-  You'll hear specific advice on treating your CV as a landing page, highlighting
-  personal contributions, crafting case-study narratives from business goals to evaluation
-  metrics, and preparing for technical assessments (ML fundamentals, SQL window functions,
-  coding). We also cover handling rejection, replying graciously, evaluating offers,
-  negotiation tactics when your current salary is low, and practical steps for PhDs
-  breaking into industry. <br><br> Listen for actionable steps to refine your data
-  science resume, prioritize take-home ROI, and use mock interviews to iterate faster."
+  like forecasting and LTV. Oleg demonstrates NextRound's mock-interview chatbot and
+  personalized feedback, explains common hiring funnels (recruiter screen → take-home
+  → interviews), and contrasts product data scientist vs. machine learning engineer
+  expectations. You'll hear specific advice on treating your CV as a landing page,
+  highlighting personal contributions, crafting case-study narratives from business
+  goals to evaluation metrics, and preparing for technical assessments (ML fundamentals,
+  SQL window functions, coding). We also cover handling rejection, replying graciously,
+  evaluating offers, negotiation tactics when your current salary is low, and practical
+  steps for PhDs breaking into industry. <br><br> Listen for actionable steps to refine
+  your data science resume, prioritize take-home ROI, and use mock interviews to iterate
+  faster.
+description: Master CV optimization, take-home projects and mock interviews to land
+  data science offers—learn SQL/ML prep, negotiation tactics and measurable project
+  impact.
 ---
 Links:
 
diff --git a/_podcast/s03e07-market-yourself.md b/_podcast/s03e07-market-yourself.md
@@ -1011,21 +1011,23 @@ transcript:
   sec: 3830
   time: '1:03:50'
   who: Alexey
-intro: "How do developers build visibility, earn promotions, and steer their careers
+intro: 'How do developers build visibility, earn promotions, and steer their careers
   by learning in public? In this episode, Shawn Swyx Wang — Senior Developer Advocate
   for AWS Amplify, author of The Coding Career Handbook, and former engineer at Netlify
   and Temporal — walks through a practical framework for personal branding and career
   marketing for developers. We unpack why self-marketing matters beyond job hunting
   and the five-part personal marketing framework: brand, domain, value, skills, and
-  channel. <br><br> You'll hear concrete guidance on choosing and validating a niche
+  channel. <br><br> You''ll hear concrete guidance on choosing and validating a niche
   (meetups, conferences, community signals), building an owned platform (blog, newsletter,
   mailing list), and distribution tactics from early social growth to the engagement
-  move \"pick up what they put down.\" Swyx also covers career transition strategies,
+  move "pick up what they put down." Swyx also covers career transition strategies,
   hiring portfolios and case studies, internal pathways like lateral moves and signature
   initiatives, and creating reusable talks and demos. Practical tools discussed include
   brag documents, demos for internal promotion, and open knowledge projects as visibility
   builders. Tune in to get actionable steps to craft a developer personal brand, grow
-  influence, and apply learn-in-public tactics to advance your career and job opportunities."
+  influence, and apply learn-in-public tactics to advance your career and job opportunities.'
+description: 'Discover personal branding & career marketing for devs: learn-in-public
+  tactics, niche choice and internal promotion to boost visibility and land promotions.'
 ---
 Links:
 
diff --git a/_podcast/s04e08-freelancing.md b/_podcast/s04e08-freelancing.md
@@ -1136,21 +1136,23 @@ transcript:
   sec: 3827
   time: '1:03:47'
   who: Alexey
-intro: "How do you build a reliable freelance career around machine learning when
+intro: 'How do you build a reliable freelance career around machine learning when
   clients expect production-ready systems, not just prototypes? In this episode, Mikio
   Braun — an ML researcher who has moved models into production at European unicorns
   Zalando and GetYourGuide and now advises companies as a consultant — walks through
   what freelancing in machine learning really involves. <br><br> We focus on practical,
   end-to-end concerns: aligning ML work with product goals, designing ML infrastructure
   that supports deployment and maintenance, and translating research or proofs-of-concept
-  into production-grade solutions. Mikio's background in both research and industry
-  gives him direct experience with the technical and product-side trade-offs that matter
-  to clients hiring an ML consultant or machine learning freelancer. <br><br> Listeners
-  will come away with concrete perspectives on where freelance ML work adds value,
-  how to scope engagements that bridge experimentation and production, and what to
-  prioritize when building ML systems for real users. This episode is essential for
-  machine learning freelancers, aspiring ML consultants, and product teams evaluating
-  external ML expertise."
+  into production-grade solutions. Mikio''s background in both research and industry
+  gives him direct experience with the technical and product-side trade-offs that
+  matter to clients hiring an ML consultant or machine learning freelancer. <br><br>
+  Listeners will come away with concrete perspectives on where freelance ML work adds
+  value, how to scope engagements that bridge experimentation and production, and
+  what to prioritize when building ML systems for real users. This episode is essential
+  for machine learning freelancers, aspiring ML consultants, and product teams evaluating
+  external ML expertise.'
+description: 'Learn freelancing strategies for machine learning: win clients, price
+  ML projects, build a portfolio and deliver production models to increase income.'
 ---
 
 Books: 
diff --git a/_podcast/s05e02-data-engineering-acronyms.md b/_podcast/s05e02-data-engineering-acronyms.md
@@ -1022,7 +1022,7 @@ transcript:
   sec: 3689
   time: '1:01:29'
   who: Alexey
-intro: "How do you decide between ETL and ELT, or when to keep a data lake versus a
+intro: How do you decide between ETL and ELT, or when to keep a data lake versus a
   warehouse—and where do tools like Airbyte, dbt, and CDC fit into a modern data stack?
   In this episode, Natalie Kwong, Growth Product Manager at Airbyte with prior analytics
   and ops roles at Harness, KeepTruckin, and AppDynamics, pulls from hands-on experience
@@ -1036,7 +1036,9 @@ intro: "How do you decide between ETL and ELT, or when to keep a data lake versu
   If you're designing a modern data platform or refining pipelines, this episode offers
   practical guidance on ETL vs ELT decisions, choosing lakes vs warehouses, leveraging
   Airbyte and dbt, and operational considerations like data quality, orchestration,
-  and cleanup practices."
+  and cleanup practices.
+description: Discover ETL vs ELT, data lake vs data warehouse with Airbyte and dbt—learn
+  CDC, orchestration, and governance to design reliable, fast modern data pipelines.
 ---
 
 Links:
diff --git a/_podcast/s06e01-solopreneur.md b/_podcast/s06e01-solopreneur.md
@@ -3,6 +3,7 @@ title: 'Solopreneur Guide: Diversify Income with Courses, Consulting, Books & Si
 short: 'Solopreneur Guide: Diversify Income with Courses, Consulting, Books & Side-Gigs'
 guests:
 - noahgift
+description: 'Discover solopreneur tactics to build a side-gig tunnel, diversify income mix with courses, teaching and consulting, and quit corporate on your terms.'
 image: images/podcast/s06e01-solopreneur.jpg
 season: 6
 episode: 1
diff --git a/_podcast/s06e02-non-technical-interviews.md b/_podcast/s06e02-non-technical-interviews.md
@@ -4,6 +4,7 @@ short: Ace Non-Technical Data Science Interviews
 guests:
 - nicksingh
 image: images/podcast/s06e02-non-technical-interviews.jpg
+description: 'Master behavioral interviews & prep to break into data roles: build an impact portfolio, use STAR stories, nail case interviews and cold emails.'
 season: 6
 episode: 2
 ids:
diff --git a/_podcast/s07e05-machine-learning-system-design-interview.md b/_podcast/s07e05-machine-learning-system-design-interview.md
@@ -2,7 +2,7 @@
 episode: 5
 guests:
 - valeriybabushkin
-intro: "How do you approach ML system design interviews that probe production constraints,
+intro: 'How do you approach ML system design interviews that probe production constraints,
   fraud detection trade-offs, and MLOps realities? In this episode, Valerii Babushkin
   — Senior Director of Data, Analytics, and AI at BP, Kaggle Competitions Grandmaster,
   and author of Machine Learning System Design — walks through what interviewers look
@@ -17,10 +17,9 @@ intro: "How do you approach ML system design interviews that probe production co
   — signposting depth, stating assumptions, iterative baselines — and guidance for
   new grads and career progression toward system design roles. <br><br> Listen to
   learn actionable frameworks, example trade-offs, and preparation strategies to improve
-  your ML system design interviews and production ML decisions."
-description: Master ML system design interviews with Valerii Babushkin, ex-Meta Head
-  of Data Science. Learn fraud detection systems, feature engineering, metrics selection,
-  and production ML best practices for FAANG interviews.
+  your ML system design interviews and production ML decisions.'
+description: 'Master ML system design: fraud detection, feature engineering & A/B
+  testing to ace interviews, build robust production models, monitoring and MLOps.'
 topics:
 - machine learning
 - career growth
diff --git a/_podcast/s07e08-from-data-science-to-data-engineering.md b/_podcast/s07e08-from-data-science-to-data-engineering.md
@@ -2,8 +2,7 @@
 episode: 8
 guests:
 - ellenkonig
-description: Transition from data science to data engineering. Learn DevOps, CI/CD,
-  collaboration skills, and cloud platforms. Career advice from Ellen König.
+description: "Master data engineering, MLOps and pipelines: learn CI/CD, cloud cost control and SQL/Python skills to switch careers and accelerate growth now."
 intro: "In this episode, Ellen König—Head of Engineering at alcemy—shares her journey
   from software and data science to data engineering leadership. She explains why
   many professionals make the switch, the skills that matter most (from DevOps and
diff --git a/_podcast/s08e02-hacking-your-data-career.md b/_podcast/s08e02-hacking-your-data-career.md
@@ -18,7 +18,7 @@ links:
 season: 8
 short: Hacking Your Data Career
 title: 'Standing Out as a Data Scientist: Proactivity, Unique Projects & Career Strategy'
-description: 'Learn how to hack your data career with proactive task selection, unique coffee-machine time-series projects, OSINT analytics, and expert LinkedIn growth tips.'
+description: 'Discover proven strategies to stand out in data science: build unique portfolio projects, master proactive task selection, and grow visibility with expert LinkedIn tactics.'
 transcript:
 - header: 'Career Journey: Sociology, Criminology, and Data Science'
 - line: This week, we'll talk about hacking your data career. We have a special Marijn.
diff --git a/_podcast/s08e06-recruiting-data-engineers.md b/_podcast/s08e06-recruiting-data-engineers.md
@@ -2,7 +2,7 @@
 episode: 6
 guests:
 - nicolasrassam
-intro: "How do you hire data engineers in Europe today — and what should candidates
+intro: How do you hire data engineers in Europe today — and what should candidates
   and hiring managers actually focus on during interviews? In this episode, Nicolas
   Rassam, a Senior Talent Acquisition Partner at Helsing with 10+ years scaling AI
   and engineering teams at Onfido and Criteo, walks through the practical realities
@@ -18,7 +18,7 @@ intro: "How do you hire data engineers in Europe today — and what should candi
   also addresses hiring without degrees, industry fit for regulated data, and how
   targeted applications beat spray-and-pray. Listen to learn what to prepare for interviews,
   how to position projects, and what hiring teams really look for when recruiting
-  data engineering talent in Europe."
+  data engineering talent in Europe.
 ids:
   anchor: Recruiting-Data-Engineers---Nicolas-Rassam-e1hnkl1
   youtube: hylxiu4VGTo
@@ -32,8 +32,8 @@ season: 8
 short: Recruiting Data Engineers
 title: 'Hiring Data Engineers in Europe: Nicolas Rassam on Interviews, Skills & Career
   Switches'
-description: Learn how to land data engineering roles with Nicolas Rassam. Master
-  SQL, Python, portfolios, interviews, and switching careers effectively.
+description: 'Learn hiring strategies for data engineering in Europe: interview prep,
+  resume tips (SQL/Python), career-switch paths and cloud fundamentals to win roles.'
 topics:
 - data engineering
 - career switch
diff --git a/_podcast/s09e03-getting-data-engineering-job-(summary-and-q&a).md b/_podcast/s09e03-getting-data-engineering-job-(summary-and-q&a).md
@@ -777,6 +777,8 @@ intro: 'How do you actually get a data engineering job today — and which skill
   remote work realities, and how to leverage non-coding experience. Listen to learn
   a practical roadmap for interviews, portfolio building, and job search tactics to
   increase your chances of landing a data engineering role.'
+description: 'Master data engineering job prep: Python, SQL tips, portfolio strategy,
+  interview formats and job search tactics to land offers faster. quick wins'
 ---
 
 Links:
diff --git a/_podcast/s09e04-freelancing-and-consulting-with-data-engineering.md b/_podcast/s09e04-freelancing-and-consulting-with-data-engineering.md
@@ -1273,7 +1273,7 @@ transcript:
   sec: 3776
   time: '1:02:56'
   who: Adrian
-intro: "How do you price freelance data engineering work, win steady clients, and
+intro: 'How do you price freelance data engineering work, win steady clients, and
   pick the right tools for messy production problems? In this episode, Adrian Brudaru
   — an economist-turned-business analyst who moved to Berlin, left corporate/startup
   cycles to freelance for five years, and now co-founds a data company releasing open
@@ -1288,7 +1288,9 @@ intro: "How do you price freelance data engineering work, win steady clients, an
   in local markets like Berlin. <br><br> Listen to learn concrete approaches to freelance
   data engineering pricing, client acquisition strategies, scoping projects, and practical
   tools to handle unstable schemas — so you can evaluate projects, set rates, and
-  grow a sustainable freelance practice."
+  grow a sustainable freelance practice.'
+description: 'Master freelance data engineering: pricing, client acquisition & tools
+  to negotiate rates, scope projects, build reusable portfolios and win repeat clients.'
 ---
 Links:
 
diff --git a/_podcast/s10e02-decoding-data-science-job-descriptions.md b/_podcast/s10e02-decoding-data-science-job-descriptions.md
@@ -1149,6 +1149,9 @@ intro: 'How can you tell if a "data scientist" job is really a data engineering
   salary transparency, remote-work fit, retention and career ladders. <br><br> Listen
   to learn concrete signals and questions to evaluate job descriptions, interviews,
   and shape better data hiring and team design.'
+description: Discover how to spot misleading job titles, hiring red flags and build
+  stronger data teams-assess tech stacks, interview rigor, salary ranges and career
+  fit.
 ---
 
 Links:
diff --git a/_podcast/s12e05-indie-hacking.md b/_podcast/s12e05-indie-hacking.md
@@ -1204,6 +1204,8 @@ intro: 'How do you build, launch, and actually monetize indie-hacker products in
   launch, monetization, and time management for indie hackers working on crypto alerts
   and generative AI—concrete steps to validate, build, and grow side products without
   external funding.'
+description: 'Build indie-hacking products: launch crypto alerts & generative AI apps,
+  validate ideas, choose tech, price effectively and monetize for sustainable growth.'
 ---
 
 Links:
diff --git a/_podcast/s13e04-starting-consultancy-in-data-space.md b/_podcast/s13e04-starting-consultancy-in-data-space.md
@@ -1108,6 +1108,8 @@ intro: How do you validate customers, run effective user interviews, and set pri
   for registering a consultancy in Germany. <br><br> Listen to get actionable methods
   for customer validation, user interviews, pricing strategy, and building a data
   consulting business that captures real client value.
+description: 'Learn data consulting: customer validation, user interviews and pricing
+  strategy to validate ideas, win clients, set value-based rates & scale your practice.'
 ---
 Links:
 
diff --git a/_podcast/s14e05-lessons-learned-from-freelancing-and-working-in-start-up.md b/_podcast/s14e05-lessons-learned-from-freelancing-and-working-in-start-up.md
@@ -1012,6 +1012,8 @@ intro: How do you transition from startup engineering to a sustainable freelance
   to get actionable guidance on building a portfolio, selecting projects, monitoring
   production models, and practical steps to find and retain clients as a freelance
   data scientist.
+description: 'Discover MLOps, model monitoring & Upwork tips to build a freelance
+  data scientist portfolio: pricing, onboarding, tools to land clients including MLflow'
 ---
 
 Links:
diff --git a/_podcast/s15e02-investing-in-open-source-data-tools.md b/_podcast/s15e02-investing-in-open-source-data-tools.md
@@ -1100,6 +1100,8 @@ intro: How do you build a sustainable business around open source developer, dat
   like Hugging Face, Supabase, Kong and Qdrant. Listen to gain actionable frameworks
   for GTM, funding strategy, monetization and early-stage investment signals for open
   source developer, data and AI tooling.
+description: 'Discover open source go-to-market for developer tooling: funding, monetization
+  models, community metrics and fundraising tactics to scale early-stage startups.'
 ---
 Links:
 
diff --git a/_podcast/s16e05-from-research-scientist-at-amazon-to-machine-learning-ai-consultant.md b/_podcast/s16e05-from-research-scientist-at-amazon-to-machine-learning-ai-consultant.md
@@ -1246,6 +1246,8 @@ intro: 'How do you turn NLP research experience into a viable generative AI free
   posts, papers, side projects). Listen to learn concrete steps for becoming an NLP
   consultant, running annotation experiments that scale, and pitching value to SMEs
   and product teams.'
+description: 'Discover how to launch a generative AI freelance business: NLP services,
+  model-in-the-loop annotation, pitch-deck strategies, client leads & scalable workshops.'
 ---
 Links:
 
diff --git a/_podcast/s16e09-become-data-freelancer.md b/_podcast/s16e09-become-data-freelancer.md
@@ -1192,6 +1192,8 @@ intro: 'How do you move from corporate data roles into a sustainable freelance d
   approaches for rates, contract checkpoints, and resources (courses, mentors, newsletters)
   to reduce risk and build a reliable pipeline. Ideal for aspiring data freelancers
   seeking practical guidance on pricing, outreach, contracts and risk.'
+description: 'Launch your data freelancer career: pricing, outreach & contracts tactics,
+  client vetting, legal risk and runway tips to win steady projects.'
 ---
 Links:
 
diff --git a/_podcast/s17e01-entrepreneurship-journey-from-freelancing-to-starting-company.md b/_podcast/s17e01-entrepreneurship-journey-from-freelancing-to-starting-company.md
@@ -1184,6 +1184,8 @@ intro: How do you build an open‑source data tool that lets Python users turn m
   <br><br> If you build Python data pipelines or maintain data warehouses, this episode
   offers concrete guidance on designing declarative JSON‑to‑relational pipelines,
   documenting them as a product, and taking an open‑source data tool to users.
+description: Discover building open-source JSON-to-Relational data pipelines in Python,
+  practical DLT patterns, anti-pattern fixes, bootstrap tips to speed adoption.
 ---
 Links:
 
diff --git a/_podcast/s20e09-taking-your-freelance-career-to-next-level.md b/_podcast/s20e09-taking-your-freelance-career-to-next-level.md
@@ -590,6 +590,8 @@ intro: How do you move from employed data pro to a sustainable data freelancer w
   vs packages), and transition planning. <br><br> Listen to get concrete guidance
   on landing clients, setting prices, structuring offers, and using AI tools to increase
   productivity as a freelance data consultant.
+description: Master data freelancer tactics, pricing strategies and AI tools to land
+  clients, price services confidently, and boost productivity for higher income.
 ---
 
 Links:
diff --git a/_podcast/s22e04-how-to-build-and-evaluate-ai-systems-in-age-of-llms.md b/_podcast/s22e04-how-to-build-and-evaluate-ai-systems-in-age-of-llms.md
diff --git a/scripts/generate_meta_descriptions.py b/scripts/generate_meta_descriptions.py
diff --git a/scripts/podcasts.txt b/scripts/podcasts.txt
