newsletterAugust 29, 2026·Towards Data Science

4 Claude Skills Every Data Scientist Needs in 2026

Four skills worth adding to your workflow today if you don't want to be left behind The post 4 Claude Skills Every Data Scientist Needs in 2026 appeared first on Towards Data Science.

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•Four skills worth adding to your workflow today if you don't want to be left behind The post 4 Claude Skills Every Data Scientist Needs in 2026 appeared first on Towards Data Science.
•This story was reported by Towards Data Science, covering developments in the newsletter space.
•AI advancements continue to reshape industries — read the full article on Towards Data Science for complete coverage.

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A Scaffold at the Gate: Building AI Applications That Can Evolve

A technical reflection on why data scientists need software engineering principles when AI agents write code. The post A Scaffold at the Gate: Building AI Applications That Can Evolve appeared first on Towards Data Science.

Towards Data Science

Your Agent Doesn't Need More Freedom

Agents got good. The hard part now is everything around them. The post Your Agent Doesn't Need More Freedom appeared first on Towards Data Science.

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Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling

Benchmarking NumPyro, affine-invariant MCMC, and dynesty against exact ground truth and watching them fail. The post Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling appeared first on Towards Data Science.

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Coding Agents Can Solve the Task — But How Much Work Did They Waste?

Real repositories, seeded agent decisions: what 50,400 runs show about wasted turns, patch churn, and which harness rules help The post Coding Agents Can Solve the Task — But How Much Work Did They Waste? appeared first on Towards Data Science.

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4 Claude Skills Every Data Scientist Needs in 2026

Key Takeaways

Related Articles

A Scaffold at the Gate: Building AI Applications That Can Evolve

Your Agent Doesn't Need More Freedom

Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling

Coding Agents Can Solve the Task — But How Much Work Did They Waste?

Discussion

4 Claude Skills Every Data Scientist Needs in 2026

Key Takeaways

Related Articles

A Scaffold at the Gate: Building AI Applications That Can Evolve

Your Agent Doesn't Need More Freedom

Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling

Coding Agents Can Solve the Task — But How Much Work Did They Waste?

Discussion

Related Articles

Towards Data Science
A Scaffold at the Gate: Building AI Applications That Can Evolve
A technical reflection on why data scientists need software engineering principles when AI agents write code. The post A Scaffold at the Gate: Building AI Applications That Can Evolve appeared first on Towards Data Science.

Towards Data Science
Your Agent Doesn't Need More Freedom
Agents got good. The hard part now is everything around them. The post Your Agent Doesn't Need More Freedom appeared first on Towards Data Science.

Towards Data Science
Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling
Benchmarking NumPyro, affine-invariant MCMC, and dynesty against exact ground truth and watching them fail. The post Three Samplers, One Posterior: NUTS vs. Emcee vs. Nested Sampling appeared first on Towards Data Science.

Towards Data Science
Coding Agents Can Solve the Task — But How Much Work Did They Waste?
Real repositories, seeded agent decisions: what 50,400 runs show about wasted turns, patch churn, and which harness rules help The post Coding Agents Can Solve the Task — But How Much Work Did They Waste? appeared first on Towards Data Science.