HeyJaredSenior Data Science Lead
I write about Data Science, Machine Learning and leading data teams. I have built teams from scratch and lead 50+ data scientists @Skyscanner. Now, I share my experience with you.
- Indexed issues, last 90 days
- 10
- Latest publication
- Sep 11, 2026
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- Checking…
- Earliest in this view
- Jul 5, 2026
Latest issues
Claude Code agent teams: when and how to go multi-agent (opens the original)
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This week I finished building an orchestrated team of agents interacting with each other within the Claude Code ecosystem. I actually liked how the final version of the system works, but it is not as simple as it sounds to get one working. And I fear many people are jumping into building agent teams without fully understanding the trade-offs. I get it, agent teams sound like the natural next step once you have subagents working. Let me be clear: they are not. Agent teams are a coordination layer
🚀 September on Sr Data Science Lead: What’s coming up. (opens the original)
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<img alt="Download 4k, 2026 September Calendar, pumpkins, books, September 2026, autumn calendars, September 2026 Calendar, September 2026 desk calendar, September calendars, 2026 calendars, September wallpapers for desktop free. Pictures for desktop free" class="sizing-
Google released TabFM: A real step forward for Tabular foundational models (but not a revolution) (opens the original)
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On June 30, 2026, Google Research published TabFM, a tabular foundation model released with a scikit-learn-compatible API, pretrained weights, and a GitHub repo. To understand why this release is worth taking seriously, you have to understand what it is pushing against. Tabular data is the format that most practising data scientists actually work with every day. For roughly a decade, the algorithm that won on that format, consistently, was gradient-boosted decision trees. XGBoost, LightGBM, CatB
Sonnet 5 is only good at one thing (beating Sonnet 4.6) (opens the original)
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On the 30th of June, Anthropic released Sonnet 5 and what it should have been a launch to get people excited, seems to have transformed in quite the opposite. When I myself read that “Sonnet 5 narrows the gap: its performance is close to that of Opus 4.8, but at lower prices” directly from Anthropic’s release blog, I thought that at least Anthropic had started to tackle what I believe is the future of LLMs: smaller and cheaper but capable enough models.But no, the community did not buy Anthropic
Module 8 - How to balance dominant bar chart categories (opens the original)
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<img alt="" class="sizing-normal" height="552" src="https://substackcdn.com/image/fetch/$s_!k3h4!,w_1456,c_limit,f_auto,q_auto:good,fl_progressive:steep/https%3A%2F%2Fsubstack-post-media.s3.amazonaws.com%2Fpublic%2Fimages%2F4b4846dc-a799-4251-b770-54df9e300515_1024x1536.pn
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