PlotSet

Co-Founder

Eeagli

Data Visualisation Consultant and Creator

Vontobel Asset Management

Associate Director - Editorial Manager

Unigestion

Worked on setting up a document automation system and wrote thought leadership pieces on private equity, hedge fund strategies and factor-based investing.

Senior Content Writer

Fidelity Worldwide Investments

Part of the thought leadership team at Fidelity. Responsible from producing white papers and ground-breaking research with investment management teams.

Senior Investment Writer

Gartmore

Sat on the fixed income desk next to the Head of Credit. Produced desk reports, serviced the needs of clients and sales, and handled press requirements.

Fixed Income Specialist

HSBC Global Asset Management

Part of a global five-person sales team that won USD 41.2 billion assets under management over the course four years from sovereign wealth funds and central banks.

Institutional Sales - Middle East, Sovereigns and Central Banks

Bestinvest

A one-year work placement where I brought in GBP 50 million in net new money from high net worth clients as a result of a successful project I ran.

Associate

Data Storyteller and Investment Writer, Founder of Eeagli (LinkedIn Top Voices 2022 - Finance)

I make data dance because when numbers come alive you can see the world for what it is.

I’m James Eagle, a data visualisation specialist, keynote speaker, and seasoned investment writer with two decades of experience in asset management and banking industries. I’ve developed unique techniques that transforming complex topics into clear, compelling stories.

What I Do:

→ Data Visualisation: I bring stories to life through visuals that cut through the noise, revealing truths you might miss that help you start conversations that matter.

→ Thought Leadership: My upcoming book, From Chaos to Clarity (launching July 10), explores how data visualisation could help save humanity from a world drowning in data.

→ Keynote Speaking: When step on stage I ignite the room, bringing data to life through my powerful animated visualisations.

→ AI Innovation: I'm building an AI language model that lets you upload and explore massive datasets, uncover the hidden stories beneath the numbers, and transform these discoveries into powerful visual narratives.

→ Social Media & Communication: I consult with companies of all sizes to help them tell better stories online, bridging the gap between complexity and clarity.

Why It Matters: Because data, when brought to life, has the power to shift perspectives, shape strategies, and ignite new ideas.

James Eagle

AI is starting to look like a closed loop of money.

Goldman Sachs Research have drawn the picture here really well. Their network map of AI partnerships is basically a wiring diagram for circular finance. 

On top of that, a lot of this hardware is being depreciated over 6 to 8 years even though the tech cycle runs on something closer to 2 or 3. Michael Burry has been shouting about this for months. The same names appear on almost every line. Chips, cloud, equity, services. All bouncing around a tiny club that is amplified by the dollar and America’s ability to pull in global capital.

This is not about fraud. It is about concentration and fragility. If the forecasts are wrong and AI infrastructure is overbuilt, whose revenue survives once the circular money slows down? And whose story quietly falls apart?

I will create any data visualisation idea you have on this story. I really want more clarity on these risks. I want to see them. Comment below please

Source: Editor Allison Nathan, Goldman Sachs Research, Top of Mind, "AI in a Bubble"

Co-founder of PlotSet | Turn complex data into beautiful, ready-to-share data visualizations. The best bit is no coding required.

The AI money machine! Well, it's almost impossible to map. But someone has got to do it. This is the circular flow of capital through the AI infrastructure
economy from 2019 to 2032. A rose-tinted version that's being priced in. What looks like a complex web is actually a surprisingly simple money machine.

Here's how it works. Tech giants (Microsoft, Amazon, Google, Meta) invest trillions in AI development and infrastructure. That money flows to OpenAI and cloud providers, who then purchase GPUs and networking chips from NVIDIA, AMD and Broadcom. Meanwhile, OpenAI generates revenue by licensing its models back to Microsoft and others, creating a closed loop. 

The numbers are staggering. Microsoft has invested over $13 billion in OpenAI since 2019. Oracle just signed a $300 billion deal with OpenAI for data centre capacity through 2029. Meta is scaling from 150,000 NVIDIA GPUs in 2023 to 1.3 million by the end of 2025, spending up to $65 billion this year alone. Broadcom's AI chip revenue jumped from $3.8 billion in 2023 to a projected $40 billion by 2026, a tenfold increase in three years.

What makes this ecosystem fascinating is how tightly interconnected it is. NVIDIA recieves infrastructure spending from nearly everyone. The chip makers get paid in advance whilst the AI companies bet on future revenue that may or may not materialise. If we assume that it does however, then this is what it looks like. Is this realistic. Let me know in the comments below.

This is the power of data visualisation and why we launched PlotSet. Is what we see here realistic? Let me know in the comments below.

Music: The Great Unknown by Hampus Naeselius, Epidemic Sounds

This looks like another tech rout, but this chart tells a more interesting story. Returns over the past month are not moving in one direction, they are spreading out.

Some giants like Google and Amazon sit comfortably above zero with double digit gains. Others including Tesla Meta and Oracle are deep in the red. Dispersion is widening, even though every bubble in this chart is a company worth more than $5 billion.

That is what makes data visualisation useful. You can see in seconds that this is not a blanket rout but a market that is starting to separate winners from losers.

In a world of richer dispersion, would you rather own the broad tech index or a concentrated basket of names you believe can justify their valuations? The question is can any of them justify there valuations?

Bitcoin has wiped out its 2025 gains and broken below 100k. The move has been brutally fast, and that speed matters because it looks like panic selling rather than a calm reassessment. See the data visualisation below.

The driver sits in the AI trade. 

Reports suggest OpenAI lost around $8bn in the first half of 2025, with revenue running in the low tens of billions, and it has been marked at about a $500bn valuation in recent secondary deals. NVIDIA now makes up roughly 8% of the S&P 500 raising concerns of concentration risk. Palantir has traded at more than 500 times earnings. 

When large investors finally began to question these valuations, they raised cash by selling their highest risk position first. That was Bitcoin.

Why Bitcoin? Because the same hedge funds, family offices and macro traders who own the big AI names also hold bitcoin as their most speculative asset. When confidence in tech wobbles, they do not sell NVIDIA on day one. They cut Bitcoin to reduce risk. Bitcoin has therefore become the pressure valve for AI anxiety.

You can see the split in the data. Bitcoin is down about 28% in six weeks and roughly $1.2tn has been wiped off the wider crypto market. By contrast, the Nasdaq is only a little off its highs despite the well publicised sell off in tech in recent days.

If Bitcoin is now the first place institutional doubt shows up, what does that tell us about where tech valuations go next? How do you read this story?

Music: Hidden Enigma by Dream Cave, Epidemic Sounds

This is a post from my personal branding coach Tima Elhajj. It's really worth reading because it mirrors my story. I usedto feel like I didn't have an identity in the companies I worked for. I was a cog in a machine. Invisible. That's why I started writing on LinkedIn back in 2016.

So this is what happened:

1. I started to connect with people in other companies, but in the same industry. If I didn't do that, I wouldn't have had the network to scale the business I have today.

2. I gained an outsider perspective, outside the company's walls. I never realised how much I didn't know by learning from others whom I would never normally have conversed with.

3. My self-esteem improved and sense of value as I now knew people on LinkedIn who valued my thoughts.

This was all before I started data visualisation and becoming a Top Voice. What I got from developing a personal brand was access to opportunities I would have never otherwise had. It was liberating. So please post and please show yourself here on LinkedIn.

Elevating Personal Brands with Elegance on LinkedIn across the UAE, Saudi Arabia, and the wider Arab region

Each week I’m seeing a pattern.

Executives who aren't job hunting. They're soul searching.

They have the title, the salary, the respect. 
But they're asking themselves: 
"What else is there?"

If anything they love their job. 
They respect their organisation and they care about the people they work with. 

They just understand something that most are too afraid to face.
There is more.
And they’re ready for it.

Ready to share the wisdom they've learned. 
Ready to influence beyond their organisation. 
Ready to build something that is bigger than them. 

One executive told me: 
"I've spent 20+ years doing this and I love it, but where to from here?"

Another said: 
"I love my job. But I also want to write the book I've been outlining in my head for a decade."

The common thread?
They're looking for expansion opportunities.

- Advisory roles that leverage their expertise. 
- Consulting that lets them choose their impact. 
- Books that capture their methodology. 
- Keynotes where they shape the next generation. 

The beautiful part? 
Building your brand makes you more valuable. 

- Your company benefits from your elevated thought leadership. 
- Your team gets inspired by your growth. 
- Your industry gains from your insights. 

And you? You get to [*** fill in the gaps ***]

And it doesn't require leaving what you love.
It requires expanding who you are.

❤️

Moody's Analytics

Associate Director Advisory Services

Assistant Director - Advisory Services

Assistant Director - Modelling Operations

Advisory Services Associate 

Advisory Services Graduate

University of Edinburgh

PhD in Statistical Physics in the School of Physics and Astronomy, as part of the Scottish Doctoral Training Centre in Condensed Matter Physics (CM-CDT, http://cm-cdt.supa.ac.uk/).

Research: 
Using numerical and mathematical techniques from statistical physics I have studied the role stochasticity plays in a variety of non-equilibrium mass transport models. Such models are of interest not only in physics but in a range of fields such as biology, economics and computer science. The models studied were constructed using simple topologies and a small set of simple rules designed to capture the important processes which occur. This simplification has allowed me to study these models by using various mathematical techniques, such as using mean-field master equations and generating functions, as well as by using Monte Carlo simulation and statistical analysis of the data produced.

Teaching: 
As a teaching assistant in tutorials I have engaged with undergraduate students face-to-face, explaining concepts from physics and mathematical techniques. I have also demonstrated in computing labs, teaching concepts and good practice in computer programming to novices.

Project Management: 
As part of the CM-CDT I have been the editor of an outreach magazine, with the goal of promoting science, and in particular Condensed Matter Physics, to school leavers considering taking up a university degree. I managed a group of volunteer authors from amongst my fellow PhD students, organising submission and collation of articles and images. I also proof read the articles, to ensure the content we print is of high quality and appropriate to our target audience. I have worked closely with a design team to develop an eye-catching and clear design.

Doctoral Researcher

I currently work in the ERS Insurance division of Moody's Analytics in the Capital Modelling Advisory Services Team

In November 2015 I completed my PhD thesis in the field of statistical physics. I studied for my PhD at the School of Physics and Astronomy, University of Edinburgh, UK, but also as a member of the inter-university Scottish Doctoral Training Centre in Condensed Matter Physics (CM-CDT, http://cm-cdt.supa.ac.uk/)

taplio

The Battle

James Eagle

Justin W.

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Performance ScoreJames Eagle's LinkedIn Performance

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taplio

The Battle

James Eagle

Justin W.

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}James Eagle's LinkedIn Performance

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Performance ScoreJames Eagle's LinkedIn Performance