# Hedge Funds Value Teamwork Over Python Skills, Even With Engineers

> We parsed 1,165 hedge fund job descriptions. Teamwork is up 31 points, tech skills are down.


```tldr
We pulled the description text on 1,165 open hedge fund job postings and ran it through a 75-skill taxonomy. The three biggest moves between late 2025 and Q2 2026: Teamwork (+30.7pp), Communication (+19.7pp), and Ownership (+20.0pp). Meanwhile FPGA (-26.8pp), Machine Learning (-24.2pp), and low-latency systems (-21.5pp) have collapsed as required skills. The buy-side stereotype is less relevant in the age of AI. Today's funds want operators who can ship.
```

Last week we published the first cut of our hedge fund hiring dashboard built from a prompt in matterfact ([Hedge Funds Are Hiring Like Tech Companies](https://www.matterfact.com/blog/hedge-fund-hiring-engineers)). The main finding was that 44% of every open role across 102 funds is an engineering role. Hedge funds are quietly becoming tech companies.

That post answered who the funds are hiring. This one answers a related question: what are the skillsets that funds value most? The answer, especially for engineering roles, was surprising.

We ran 1,165 of those postings, every one with real description text, through a curated taxonomy of about seventy-five skills, credentials, and competencies. Programming languages. AI and machine learning frameworks. Data and infrastructure. Quant math. Finance and markets. Soft skills. Education. Each posting gets counted once per skill it mentions, then we slice by time. The buckets are 2025 H2, 2026 Q1, and 2026 Q2 through May.

The result is a picture of how the buy-side skill stack is evolving. Almost none of it matches the traditional narrative.

```chart
hedge-fund-skills-top25
```

## The Lone Quant Is On His Way Out

The single most surprising number in the dataset is that three quarters of every hedge fund job description, 74% of the postings we parsed, now mentions teamwork or collaboration as a required attribute. A year ago it was 48%. Teamwork is now the most-cited skill across the entire industry, ahead of Python, even for engineers.

You can pair it with two other moves that tell the same story. Communication went from 26% of postings to 46%. Ownership and accountability went from 3% to 23%. These three competencies are the top three risers in the dataset.

```chart
hedge-fund-skills-risers
```

This finding is in contrast with the optics of the HF industry. The cultural image of the buy-side technologist is a head-down developer who knows more math than the people around him and is happiest with a Bloomberg terminal and his Jupyter Notebook. Funds today describe a different persona in their own postings: a teammate who communicates, takes ownership of an outcome, and ships work with other humans.

Multi-manager pod shops like Millennium, Citadel, Balyasny, and Schonfeld now dominate the AUM tables, and those structures only work if dozens of small teams coordinate on risk, data, and infrastructure. The platform is the alpha, and platforms are built by people who can talk to each other and work well with each other.

```request-access
heading: Want a live read on how a fund is restructuring?
description: matterfact turns any hiring signal into a refreshed artifact. Scrape postings, model the trend, share the dashboard with your team.
buttonText: Request access
```

## Soft Skills Up, Technical Skills Down

The biggest faller in the dataset is FPGA and hardware acceleration, down 26.8 points. Low-latency systems fell 21.5 points. Both were once a signal that a fund was working on its trading edge and both are cooling in favor of softer skills like project ownership.

```chart
hedge-fund-skills-fallers
```

Low latency still matters at firms like Optiver, IMC, Tower, Citadel Securities, and Qube Research; they will keep paying for nanoseconds. But the marginal posting at the marginal fund is no longer about shaving 500 nanoseconds off a quote-to-trade path. That race has been won, the infrastructure exists, and the talent that built it is now being retained rather than freshly hired.

The same pattern shows up in the cloud numbers. AWS mentions are up 9.5 points. Kubernetes is up 9.4 points from a base of effectively zero. Five years ago the cloud was a punchline on a trading desk and today even latency-sensitive shops are running risk, research, and tooling on hyperscalers. The plumbing is changing.

## The Machine Learning Paradox

Machine Learning as a required skill dropped 24.2 points and PhD requirements dropped 11.2 points. Deep learning, PyTorch, and TensorFlow each sit at 2 to 3% of postings.

A year ago "Machine Learning" was the marketing layer on a job description. Funds put it in because candidates wanted to see it and because investors wanted to see it. Today AI is plumbing, it is in the IDE, it is in the research workflow, it is in the data pipeline. Funds no longer need to hire "an ML engineer", or a lot less so than before. They still need a backend engineer who knows how to use foundation models, vector stores, and orchestration frameworks competently. But the job description doesn't say "ML." It says Python, AWS, and "ships fast."

That theory is supported by the rest of the data. Python rose 13.2 points and now appears in 60% of all hedge fund postings. NLP and LLM mentions are up to 8% from near zero. The infrastructure skills, including AWS, Kubernetes, CI/CD, and SQL, are all rising. Hedge funds are hiring the operators who will deploy AI inside the firm rather than the researchers who will invent new architectures. Most of the architectures they need have already been invented by Anthropic, OpenAI, Google, and Meta.

```skill-group-grid
hedge-fund-skill-groups
```

This also explains the PhD decline. When the model is downloadable, the credential matters less than the deployment skill. You can hire a master's-level engineer who has shipped three LLM-powered systems and get more leverage than a freshly minted PhD who has trained one from scratch. The funds know this and their job postings reflect it.

In terms of experience, the 3-5 year cohort is on the rise.

```request-access
heading: See where AI is actually shipping inside funds.
description: Point matterfact at any public signal and get a live artifact back. One prompt, refreshed weekly, ready to share with your team.
buttonText: Request access
```

## About this data

This data comes from an artifact that was built in matterfact from one prompt. The scraper was built on the fly and then the data was collated and presented as a dashboard. Specifically on the scraper, we run a curated keyword/regex taxonomy across each job's full description text for ~75 skills, competencies, and credentials grouped into seven buckets (Programming Languages, AI / Machine Learning, Data & Infrastructure, Quant & Mathematical, Finance & Markets, Soft Skills / Competencies, Education & Credentials). A skill is counted once per posting if any of its patterns match. Time comparison uses each posting's posted-by date bucketed into 2025 H2 (62 jobs), 2026 Q1 (274 jobs), and 2026 Q2 Apr–May (819 jobs).

```artifact
url: https://app.matterfact.com/artifacts/hedge-fund-jobs?owner=stan%40acadia.im
heading: Explore the live skills and experience dashboard
description: The same artifact, refreshed weekly, built from a single matterfact prompt.
buttonText: Open dashboard
```

What would you ask about HF job postings? Request access to matterfact and find out.

```request-access
heading: Build the artifact you wish you had on your coverage.
description: matterfact turns research questions into live dashboards. Scrape the open web, model the trend, share with your team. Request access to run it on the signals you care about.
buttonText: Request access
```