He Raised $110 Million To Develop And Promote Open-Source Standards And Tools For Data Analytics And Is Now Supporting Other Tech Founders

If you’ve ever done data analysis in Python, there’s a good chance you’ve used Pandas, the groundbreaking open-source library that transformed how data scientists work. But behind Pandas is Wes McKinney’s story of intellectual curiosity, risk-taking, and a relentless drive to build useful tools for others.

That story belongs to Wes and goes far beyond a GitHub repo. In this conversation, he opened up about his journey from math competitions in Ohio to MIT, from a skunkworks project at AQR to shaping Python as the lingua franca of data science.

Wes also talks about the early startup experiences of building and scaling Voltron Data into a $110M Series A rocket ship. He reveals his experiences with open sourcing, knowing the opportune time to turn the page and move on to the next chapter, and managing relationships.

Listen to the full podcast episode and review the transcript here.

The Accidental Technologist

Wes’s path wasn’t preordained. Born near Philadelphia and raised in Knoxville and Northeast Ohio, his early academic pursuits leaned heavily toward math.

In high school in Cuyahoga Falls near Akron, Ohio, Wes competed in math competitions, driven more by intellectual curiosity than structure or mentorship. He did very well, reaching the state and national levels. He was also into foreign languages.

At MIT, Wes initially envisioned a future in theoretical mathematics and doing something more academic. But an early realization set the stage for what would come: he wanted to do something applied with real-world impact.

That pull toward impact—and Wes’s budding interest in computer programming—would ultimately steer him away from pure math and into the world of data science, software engineering, and entrepreneurship.

As Wes recalls, he enjoyed the structured aspect of problem solving, abstract thinking, and building up a stack of tools that fit together to solve increasingly more complex problems.

A skunkworks Project That Shaped a Generation

Wes’s entry into finance after college took him to AQR Capital Management, a top quantitative hedge fund. There, he began building a Python-based research framework—not as an assigned project, but as a productivity experiment.

Ultimately, the company decided to use Python to rebuild the future models that ran the business. Wes believes AQR and much of the financial industry have been running on Python-based core principles over the last decade.

Unbeknownst to Wes, his skunkworks tool would become the foundation for Pandas at that time. Convincing AQR leadership to open-source the core data analysis framework was no easy feat.

It took months of internal lobbying, legal reviews, and strategic analysis. But the bet paid off—not just for AQR, which gained credibility and hiring leverage in the engineering community, but for the entire data science world.

Pandas catalyzed the growth of the Python data ecosystem and, as Wes puts it, “helped make Python the number one language of AI and data science.” People outside the company would contribute to the project and improve it.

Pandas and several other projects in that era fit together to create a productive environment for data analysis and data science work. Google, Meta, and all the other companies ended up choosing Python as the language to build their AI frameworks.

Dropping Out to Go All In

Despite his growing success with Pandas, Wes wasn’t done exploring. He briefly started a PhD in statistics at Duke, but quickly realized that his real calling was in industry. He wanted to develop a better academic and applied foundation for data science work.

Conference talks about using Python for quantitative finance, and the early adoption of Pandas brought inbound interest. Soon, Wes dropped out, moved back to New York, and went all-in on open source and entrepreneurship.

With Chang She, a former colleague from AQR, Wes co-founded DataPad, a business intelligence platform built around Python extensibility. The company raised a seed round from Accel and relocated to San Francisco in 2013.

Wes and Chang hired a small team and started building the business analytics product, working with some initial design partners. Despite early traction, DataPad faced a brutal market reality: the business intelligence space was overcrowded, and differentiation was challenging.

By late 2014, the team contemplated raising a bridge round, but instead opted for a strategic acquihire exit to Cloudera—a move that preserved the mission and found a home aligned with Wes’s passion for open-source software and data infrastructure.

From Arrow to Ursa Computing: Building the Future of Data Connectivity

Cloudera proved to be a springboard rather than a destination. While there, Wes, with a group of other open source developers, co-founded Apache Arrow, a project aimed at creating a new standard for accelerated data connectivity and processing.

However, Cloudera wasn’t the ideal environment to incubate it in the long term. Enter Two Sigma, which brought Wes in full-time to keep building Arrow. As Arrow gained adoption, so did interest from companies like NVIDIA, Bloomberg, and others.

These companies were interested in committing capital to fund Arrow development. Initially, Wes decided to create Ursa Labs, a nonprofit industry consortium to combine these capital commitments into one place, and to continue working on the project without necessarily founding a for-profit company.

Wes built Ursa Labs inside RStudio, which is now called Posit, a leading data science platform company. Posit provided funding for Ursa Labs and handled the operational side of running the team, dealing with the healthcare, benefits, and other aspects.

But by 2020, it became clear there was a startup opportunity. Armed with conviction, co-founder Neal Richardson, and backing by GV and Walden Catalyst, Ursa Computing was born.

The goal? Building enterprise solutions for accelerating data access and processing while supporting the growth of the Arrow ecosystem.

The Journey to Voltron Data

Retracing the steps in his journey, Wes explains that they went from Ursa Labs to Ursa Computing, and then to Voltron Data. They initially raised the seed round for Ursa Computing, a startup that spun out of Ursa Labs.

At the end of 2020, Wes contacted Josh Patterson, who was leading the RAPIDS team at NVIDIA. RAPIDS is a GPU acceleration framework for analytics at NVIDIA, and Josh and his team were interested in founding a company.

Wes had business ideas about pursuing Ursa Computing around enterprise support for Apache Arrow and improving and accelerating enterprise data connectivity.

Josh and Wes decided to join forces and also add in BlazingSQL, a startup that had worked closely with the RAPIDS team to build a GPU-accelerated SQL engine.

Together, they created a super company that could compile all the concepts. Lip-Bu Tan from Walden International, now CEO of Intel, stepped up to spearhead the effort from the fundraising side. They leveraged the potential for their ideas to bring significant capital to the table.

In the initial few months of 2021, Wes and his partners created a reorganized company and geared up for the next funding rounds.

Scaling, Focus, and the Power of Letting Go

Voltron Data’s first year was a whirlwind. The team scaled from 35 to 130 people in 18 months. They pulled together components from various efforts—Ursa Computing, NVIDIA’s RAPIDS leadership, and BlazingSQL—and raised $110M in Seed and Series A funding.

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But with scale came the need for focus. By the end of 2022, the macro environment had shifted—interest rates were up, capital was tighter, and the company had to hone in on narrower, high-value verticals like GPU-accelerated data workloads.

For Wes, this meant some of the directions he was passionate about no longer aligned with the company’s short-term roadmap.

Recognizing that his core contributions—creating foundational tech, forming the leadership and engineering teams, raising capital—had been made, Wes chose to transition from full-time operator to senior advisor to be able to spend time on a broader portfolio of projects.

As a way to stay involved in open source data science, Wes seized an opportunity to rejoin Posit, which had recently made Python a first-class citizen in its open source and enterprise software offerings. Additionally, he looked for ways to spend more time helping fellow entrepreneurs.

From Builder to Backer: Investing in the Next Generation with Composed Ventures

Looking around, Wes noted that many new companies were being founded in and around the Arrow ecosystem and using Arrow and related technologies as part of their core technology platform. He didn’t just walk away from startups—he leveled up.

Now an active investor, Wes has made over 40 angel investments and launched Composed Ventures, a venture fund focused on data infrastructure, data science, accelerated computing, developer tools, and deep tech. Wes prefers to work with deep tech companies or technical founding teams.

Wes has also developed pattern recognition to see what works and doesn’t, and identify founders with a higher chance of success.

What does Wes look for in founders?

• Strong Technical Foundation – Especially technical CEOs who understand the stack deeply and operate on a similar intellectual wavelength.
• Clarity of Vision – Founders who can articulate what’s broken in the prior generations of technologies and how their solution changes the game.
• Ability to Execute – Great ideas are one thing; executing on them is another. Track record and resourcefulness matter.

Wes is particularly bullish on a composable data stack—where tools and systems are modular, interoperable, and future-proof, a philosophy rooted in Arrow itself.

Advice to Founders: Know Yourself, Choose Carefully

If Wes could advise his younger self—or any aspiring founder—it would be this:

• Know your strengths and gaps, and be honest and realistic. You can’t be great at everything, so build complementary teams to fill the gaps.
• Choose partners wisely. Alignment in values, communication, and long-term vision is crucial.
• Play the long game. Relationships and reputations matter. Investing in being a helpful, trustworthy, reliable person pays dividends—often in surprising ways.

Final Thoughts

Wes McKinney’s journey is a rare blend of technical brilliance, open-source ethos, entrepreneurial grit, and long-term strategic thinking.

From laying the foundation of Python’s rise in data science to scaling a deep-tech startup and backing the next wave of builders, his story is a masterclass in navigating the intersections of code, community, and capital.

As the data ecosystem continues to evolve, one thing is sure: Wes will be there, whether building, advising, or investing, helping to shape the tools that power tomorrow’s breakthroughs.

Listen to the full podcast episode to know more, including:

• Open-sourcing Pandas at AQR was a pivotal moment that helped establish Python as the dominant language for data science.
• Wes dropped out of a PhD program to fully pursue open source and entrepreneurship, driven by early traction from the community.
• His first startup, DataPad, exited via acquihire after recognizing the challenges of differentiating in a crowded BI market.
• Apache Arrow emerged as a foundational open-source project for modern data infrastructure, eventually leading to Voltron Data.
• Voltron Data raised $110M in funding to tackle GPU-accelerated data workloads and support the Arrow ecosystem at scale.
• Wes stepped out of operations at Voltron to split his time between building tools for open source data science at Posit and investing in startups aligned with his deep-tech thesis.
• His investing playbook centers on technical founders with strong execution skills and a clear vision for the future of data systems.

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