The Model and the Override
The key, Jim Simons said, was that he "never overrode the model." He shared this with a reporter from The New Yorker in 2017, sitting in his top-floor corner office on Fifth Avenue, beneath a painting of a lynx that has killed a hare — a canvas his wife Marilyn had banished from their Long Island mansion, which he'd rehung here, in exile, where he could enjoy it in peace. The reporter assumed the painting was a metaphor for Simons's approach to the markets. Simons corrected him: he simply liked it. This was the kind of misreading Simons attracted throughout his life — people searching for a grand theory behind every gesture, some key that would unlock the mystery of how a mathematician from suburban Boston had built the most profitable trading operation in the history of finance. The truth was at once simpler and more elusive. Simons had spent decades constructing algorithms capable of detecting patterns invisible to human cognition, patterns buried in the noise of price data like faint radio signals from a distant galaxy. And then, having built the machine, he did the hardest thing any builder can do: he trusted it. Once he settled on what should happen, he held tight until it did.
This discipline — the refusal to interfere with what the data was telling him — generated returns so staggering they resemble typographical errors. From 1988 through 2023, the Medallion Fund, Renaissance Technologies' signature product, averaged annual returns of 66% before fees and nearly 40% after them, which is to say after the firm extracted a management fee of 5% and a performance fee of 44%, among the highest in the industry.
Bloomberg Markets called Medallion "perhaps the world's greatest moneymaking machine." One dollar invested in 1988 would have grown to approximately $42,000 by 2021, net of those punishing fees. A dollar in the S&P 500 over the same period would have grown to $40. The fund never had a losing year. Not once in thirty-four attempts.
Warren Buffett,
George Soros, Peter Lynch,
Ray Dalio, Steve Cohen — all fall short.
And yet the man who built this machine was not, by temperament or training, a financier. He was a geometer, a code breaker, a department chairman, a chain-smoker with an Archimedes screw on his desk and a habit of grinding his jaw when he was deep in thought about six-dimensional spheres. He didn't own a Bloomberg terminal. He couldn't program to save his life. He thought algorithmically, but on a whiteboard, with chalk.
Jim Simons died on May 10, 2024, at the age of 86, in New York City. By then his net worth exceeded $31 billion, making him the 49th-richest person on Earth. He had given away more than $6 billion through the Simons Foundation, co-founded with Marilyn in 1994 — to autism research, basic science, mathematical education, a giant telescope in the Chilean desert hunting for gravitational echoes of the Big Bang. He had built the Flatiron Institute, a computational science center in lower Manhattan employing more than two hundred researchers, with a fifty-year funding guarantee and the computing power of a mid-sized research university. He had endowed a $500 million unrestricted gift to Stony Brook University — the largest such donation to a public university in American history. He had, in his own accounting, lived three professional lives: mathematician, investor, philanthropist. Each one, by any ordinary standard, would have been sufficient.
But the model — the algorithm for how to live, for how to manage brilliant people, for how to turn abstraction into wealth and wealth into knowledge — was the throughline. He never overrode it.
By the Numbers
The Simons Empire
66%Medallion Fund average annual return before fees (1988–2023)
$100B+Total trading profits generated by Renaissance Technologies
$31.4BPersonal net worth at time of death
$6B+Total philanthropic giving through the Simons Foundation
$500MUnrestricted gift to Stony Brook University (2023)
200+Scientists employed at the Flatiron Institute
0Losing years for the Medallion Fund (1988–2023)
The Boy Who Doubled Numbers
James Harris Simons was born on April 25, 1938, in Newton, Massachusetts, the only child of Marcia and Matthew Simons. His father had worked in film distribution for 20th Century Fox, selling movies to theaters, before entering the shoe business with his father-in-law. His mother had attended art school and was, by Jim's later estimation, "a pretty good painter," though she never exhibited commercially. The family was Jewish, comfortably middle-class, suburban in the old Massachusetts sense — a world of shoe factories and garden supply stores, of families that measured success in modest increments of visible industry.
The boy was different. He passed time by doubling numbers in his head, over and over, watching the integers climb toward incomprehensibility. He pondered Zeno's paradox — the one about Achilles and the tortoise, the infinite series converging on a finite sum — and found it not confusing but beautiful. "I liked everything about math," he said decades later. "The only thing I thought about was I would be a mathematician." As a teenager, he took a job in the basement stockroom of a garden supply store in Newton, tasked with remembering where things went. He was terrible at it, couldn't keep the inventory straight, and was promptly demoted to floor sweeper — "which I loved," he recalled, "it was easy, took no brain work." When his employers asked about his future plans and he told them he intended to study mathematics at MIT, they found this the funniest thing they'd ever heard. The boy who couldn't remember where to put the sheep manure wanted to be a mathematician.
He entered MIT at seventeen, in 1955, and finished the four-year program in three. He had heard that the legendary geometer Shiing-Shen Chern was heading to UC Berkeley, and decided to follow him there. Chern delayed his arrival by a year, so Simons ended up writing his thesis under Bertram Kostant instead, completing his Ph.D. in 1961 at the age of twenty-three. Against Kostant's advice, he chose to solve a problem in the geometry of multidimensional curved spaces that had long defeated other mathematicians. He solved it. The thesis was on the transitivity of holonomy systems — a subject so abstract that to describe it is to describe the curvature of spaces that exist only in the mind's eye, the way parallel transport of a vector around a loop in a curved manifold fails to return it to its original orientation. Topology. Differential geometry. The subtle architecture of surfaces.
His cousin Richard Lourie — a writer, raised alongside him — told a story about their grandfather, who ran the shoe factory. On paydays, the old man would let the two boys hold piles of cash "as high as our heads." Lourie recalled: "We both loved it!" But at other times, young Jim would withdraw so completely into himself that Lourie worried he was ill. "He would just say, 'I was thinking.'"
Ideas and money. Thinking and cash. From the beginning, they were intertwined.
Codes and Consequences
Between the doctorate and the fortune came a detour into the classified world. In 1964, after brief stints teaching at MIT (as a Moore Instructor) and Harvard, and a short-lived venture into floor tile manufacturing in Colombia — he and two Colombian friends from his MIT days tried to build a factory; the assembly took so long he got bored and came back — Simons joined the Institute for Defense Analyses in Princeton, the
Cold War's premier code-breaking shop, a civilian front for the National Security Agency. "Our job was to break other countries' codes and to design our own," he said. The deal was elegant: half your time on their cryptographic problems, half on your own mathematics. Simons thrived. He solved a long-standing problem in the field — one he could never discuss, because it remains classified — and his own mathematical research accelerated. He published prolifically. The IDA gave him what he craved: hard problems, smart colleagues, and the freedom to wander.
But the Vietnam War intruded. In 1967, Simons published a letter in The New York Times dissenting from a pro-war article by his boss, General Maxwell Taylor. Then a stringer from Newsweek came calling, and Simons — with the serene recklessness of a man who trusts his own judgment above all institutional authority — laid out his plan. While the war continued, he would devote one hundred percent of his time at IDA to his own mathematics. Once the war ended, he'd flip the ratio. "Then I'd work an equal amount of time only on their stuff, and it'd all balance out," he recounted years later, laughing. His superiors were not amused. He was fired in 1968.
"Getting fired once can be a good experience," he later told an MIT audience. "You just don't want to make a habit of it."
The firing was consequential in ways neither Simons nor the NSA could have anticipated. It sent him to Stony Brook.
Berkeley of the East
In 1968, at the age of thirty, Jim Simons became the youngest department chairman in the history of the State University of New York at Stony Brook. The school was young and ambitious. Governor Nelson Rockefeller wanted it to be the "Berkeley of the East," a flagship of the state university system, and he was pouring money into expansion. But the mathematics department was mediocre — a blank canvas, which is exactly what Simons needed.
Tony Phillips, a mathematician who worked with Simons at Stony Brook, recalled: "He already was a combination of ringleader and master of ceremonies and energizer." Simons attacked the problem the way he would later attack every problem: by recruiting brilliant people and removing obstacles. He hired world-class geometers and topologists. He built relationships across disciplines, most consequentially with the Nobel laureate C.N. Yang, who directed the Institute for Theoretical Physics on campus. Their conversations about the intersection of geometry and physics planted seeds that would bear fruit for decades — in Simons's own research, in his philanthropy, and eventually in the Simons Center for Geometry and Physics that he funded at Stony Brook.
During these years, Simons did the work that made his mathematical reputation. In 1974, he and Chern — the great geometer whose Berkeley seminar he had once crashed as a graduate student, initially mistaking the Chinese name for an abbreviated Eastern European one — published "Characteristic Forms and Geometric Invariants," introducing what became known as Chern-Simons invariants. The theory captured the subtle properties of three-dimensional spaces: the shape left if you excised a complicated knot, the way certain topological features resisted deformation. "I have to point out, none of these applications ever occurred to me," Simons said of the theory's later migration into string theory, quantum computing, and condensed-matter physics. "I do the math, they do the physics."
In 1976, he received the Oswald Veblen Prize in Geometry, one of the highest honors in American mathematics. He was thirty-eight years old and had achieved, by any measure, a distinguished career. "Yeah, I was a good mathematician," he said later, with characteristic self-deprecation. "I wasn't the greatest in the world, but I was pretty good."
I wasn't the greatest in the world, but I was pretty good.
He was also restless. "Academics has its charms," he once said, "but it doesn't have enough charms that I regret leaving that field." Something else was pulling at him.
Soybean Futures and the Strip Mall
All along, even at Berkeley, even at the IDA, even while proving theorems and building departments, Simons had been thinking about money. While a graduate student, he had taken a $5,000 wedding gift and driven from Berkeley to San Francisco each morning to a Merrill Lynch brokerage office, where he traded soybean futures. "They went up!" he recalled. "And then they went back down." As a teenager, he had held his grandfather's cash. As an MIT instructor, he had invested in the Colombian floor tile venture. The impulse was persistent, almost biological — not greed exactly, but something closer to a compulsion for pattern recognition applied to a new domain.
In the late 1970s, not long after winning the Veblen Prize, Simons found himself stymied by a mathematical problem involving simplexes and wanted a break. He founded a small investment firm called Monemetrics in an office park near Stony Brook — a strip mall, really, next to a women's clothing boutique and two doors down from a pizza joint. It was about the last place you'd expect to find the genesis of a financial revolution. Oil wells pumped away in a nearby parking lot when operations briefly relocated to Huntington Beach, California, and the smell of crude permeated everything. He was forty years old.
His colleagues and family thought he was making a huge mistake. Why give up a prestigious career to try to beat the market? The prevailing academic orthodoxy — the efficient market hypothesis, developed by Eugene Fama in the 1960s — held that all available information was already reflected in asset prices, making sustained outperformance essentially impossible. Simons didn't buy it. "I looked at the price charts and analyzed them, and they didn't look random to me," he said. "They looked kind of random, but not completely random. I felt there had to be some anomalies in this data which could be exploited."
He tried fundamental trading first — reading newspapers, following tickers, making bets on currencies and commodities based on intuition and judgment. It worked, for a while. He and his early partner Leonard Baum, a mathematician he'd known from the IDA and a proponent of short-term forecasting in chaotic environments, accumulated over $43 million in profits between 1979 and 1982. But the experience was miserable. "It was fundamental trading, not systematic," Simons said. "It was very gut-wrenching. You come in one morning, you think you're a genius. The markets are for you. And the next morning you come in, you feel like a jerk. The markets are against you."
Baum's strategy — buy low and hold until it appreciates, however long that takes — eventually led to catastrophic losses when the value of his positions fell 40%, triggering a contractual clause that forced Simons to liquidate everything. Baum left the firm in 1984. The setback was severe enough that Simons halted trading entirely and considered giving up on markets altogether.
He didn't. "I don't want to have to worry about the market every minute," he told a colleague. "I want models that will make money while I sleep. A pure system without humans interfering."
Data Is the Telescope
What followed was a decade of grinding, iterative construction — the assembling of a machine that would eventually generate more wealth than any investment operation in history, but that for years produced only frustration, modest returns, and a series of personnel crises that tested Simons's famous patience.
The problem was data, or rather the lack of it. In the early 1980s, historical price data was not readily available in electronic form. Simons sent a staffer to the Federal Reserve office in lower Manhattan to painstakingly record interest-rate histories by hand. For more recent pricing data, he tasked his office manager, Carole Alberghine, with recording closing prices of major currencies from the Wall Street Journal each morning. She would climb on sofas and chairs in the firm's library to update figures on graph paper hanging from the ceiling and taped to the walls. The arrangement worked until Alberghine toppled from her perch, pinching a nerve and suffering a permanent injury. It was homemade, jury-rigged, absurd — and it was the beginning of big data applied to finance, years before the phrase existed.
Simons knew what he needed: reams of historical data so his computers could search for price patterns across vast swaths of time. He needed clean data — free of the errors that could send an algorithm careening in the wrong direction. "Suppose it's a series of stock prices," he said. "31¼, 62½. Wait, stocks don't double in a day — so there's an error in the data! There's all kinds of ways to get bugs out of data, and it's important, because they can really screw you up." He staffed his operation not with MBAs or traders but with mathematicians, physicists, astronomers, and computer scientists — people who understood signal processing, pattern recognition, and statistical inference. "I like to say that you can teach a physicist finance," he told an audience at an Abel Prize event in 2022, "but you can't teach a finance person physics."
James Ax, another prize-winning mathematician, joined in the mid-1980s and helped develop early trading models. Together they launched the Medallion Fund in 1988 — named after the prestigious mathematical awards both had received. The early returns were uninspiring: 9% net of fees in 1988, while the S&P 500 returned over 16%. In 1989, the fund lost 4%. Tensions mounted. Ax was bought out. Simons brought in Elwyn Berlekamp — a prominent game theorist from Berkeley, a man who had spent years developing error-correcting codes and applying mathematics to games of strategy — to redesign the trading system from the ground up. It worked. In 1990, Medallion returned 55% net of fees. But then Berlekamp, pestered by Simons's constant calls about gold prices and one futures market or another, quit. "The hell with it," Simons reportedly told a friend. "I'm going to run it myself."
He did. And over the next few years, he hired the people who would make Medallion legendary.
The Unreasonable Effectiveness of Physicists
Peter Brown had been studying under Geoffrey Hinton at IBM's research lab — this was the late 1980s, before Hinton became famous as the godfather of deep learning — working on speech recognition, the problem of converting acoustic signals into words. Robert Mercer, Brown's colleague, had spent years at the same lab on the same problem. Both men understood something that few people in finance grasped: that the techniques used to decode human speech — hidden Markov models, statistical pattern recognition, the parsing of noisy signals into meaningful structure — were directly applicable to the decoding of financial markets. Simons recruited them both in 1993.
"Language is very predictive," Simons said, explaining his logic. He foresaw that Brown and Mercer could apply their speech-recognition skills to markets, treating price movements as a kind of language whose grammar could be learned. In an email years later, Brown, who became Renaissance's CEO, said: "Jim's genius was in seeing the possibilities for quantitative trading long before others did and in setting up a company in which he provided outstanding scientists with the resources, environment, and incentives to produce." He added: "His role was more in setting the general direction of the company than in developing the technology."
This was the critical insight — not a mathematical breakthrough but an organizational one. Simons built Renaissance as a scientific laboratory, not a trading floor. Everyone knew what everyone else was doing. There was a single model, not competing strategies. Compensation was drawn from a common pool, pegged to the overall fund's performance rather than individual contributions. "By Wall Street standards, Jim wasn't greedy," a former executive told Gregory Zuckerman, the
Wall Street Journal reporter who wrote
The Man Who Solved the Market. "So senior guys were mostly very happy and didn't fight with each other."
The culture was deliberately quirky, almost academic. Simons organized company trips to Bermuda, the Dominican Republic, Vermont. Renaissance employees once competed to see who could ride a bicycle along a particular path at the slowest speed without falling over. Weekly lectures brought in speakers from across the sciences. The office felt less like a hedge fund and more like a university department that happened to be printing money.
It's not his genius. It's his ability to manage genius.
The results were otherworldly. In 1994, Medallion generated a return over 70% net of fees. In 2000, its highest year, the fund returned 98.5%. In August 2007, as mortgage markets imploded and Goldman Sachs's $30 billion quant fund hemorrhaged money, Medallion lost $1 billion — 20% of its value — in three days. The partners gathered in Simons's smoke-filled office, ready to override the computers. They didn't. The models kept trading. By year-end, Medallion was up 85.9%.
Simons made his first million by his early forties, his first billion by his sixties. In 1993, he stopped accepting new money from outside clients. In 2005, he kicked out external investors entirely, limiting Medallion to employees only, returning profits every year, capping the fund at roughly $10 billion. He opened larger funds for outside investors — the Renaissance Institutional Equities Fund, the Renaissance Institutional Diversified Alpha Fund — but these performed far less impressively. In 2020, while Medallion gained 76%, the public funds suffered double-digit losses. The discrepancy was a source of embarrassment and legal trouble, though Simons was characteristically untroubled. "It's like the weather," he said of the difference. "The nearer in, the higher the certainty."
The Grief Inside the Machine
The fortune accumulated. But fortune, in the older sense of the word — luck, fate, the turning of the wheel — was less cooperative with the rest of his life.
In 1996, his son Paul, from his first marriage to computer scientist Barbara Bluestein, was killed in a bicycle accident. He was thirty-four. Seven years later, in 2003, his son Nick drowned while on a trip to Bali. He was twenty-four. Two sons, dead before their father. The mathematics of probability offers no comfort for such events; they are not anomalies in a data set but ruptures in the fabric of meaning itself.
Simons returned to mathematics after Nick's death. "When you're really thinking hard about mathematics, you're in your own world," he said. "And you're cushioned from other things." In his sixties, mourning, he published a widely cited paper, "Axiomatic Characterization of Ordinary Differential Cohomology," in the Journal of Topology. He was not doing recreational math. He was doing the kind of work that gets cited by other mathematicians for decades. Marilyn could tell when he was thinking about math: his eyes would glaze over and he would start grinding his jaw.
The losses reoriented his philanthropy. The Simons Foundation's enormous investment in autism research — $725 million over two decades, making him the world's largest private funder of autism science — was catalyzed by the diagnosis of their daughter Audrey, who is on the spectrum. But the scale of the giving, and the intensity with which Simons pursued it, carried the weight of a man who understood that no amount of money could have prevented what happened to Paul and Nick, and who was determined that the money would nonetheless mean something.
Galileo Had His Patrons
In 2010, Simons retired from Renaissance Technologies, turning management over to Brown and Mercer. He was seventy-one. He told people he was plenty busy, thank you, managing charitable assets and evaluating grant applications. But his family sensed a drift. "He likes to work," Marilyn said. His cousin Lourie put it more bluntly: "He would say that he had lots of projects, but no one project."
What he had, besides the foundation, was a domestic nonprofit office with an endowment of nearly $3 billion, a much larger charitable entity in Bermuda — the Simons Foundation International, with an estimated $8 billion in assets, none of it taxed — and a growing unease about how little impact even hundreds of millions of dollars in grants seemed to have on the actual pace of scientific discovery. The problem, he came to believe, was not funding but infrastructure. Scientists were drowning in data — trillions of base pairs, light measurements from billions of stars, terabytes from a single experiment — but analyzing it with jury-rigged code farmed out to graduate students. "Some of them are pretty good code writers, and some of them are not so good," he said. "But then they leave, and there's no one to maintain that code."
In 2012, he and Marilyn convened an informal conference at the Buttermilk Falls Inn in upstate New York. The technique was vintage Simons: assemble the smartest people you can find, ask them what's not being funded, then make a decision with your gut. "Taste in science is very important," he said. "To distinguish what's a good problem and what's a problem that no one's going to care about the answer to anyway — that's taste. And I think I have good taste."
David Baltimore, the Nobel laureate and former Caltech president, chaired the meeting. The geneticist Eric Lander attended, along with physicists, mathematicians, biologists, and astronomers. People pitched ambitious projects: immune-system engineering, dark-matter exploration, mapping the human genome's evolution through time. But one proposal resonated above the others.
Ingrid Daubechies — a Belgian-American mathematician at Duke, one of the most influential wavelet theorists alive, a woman who understood both the abstraction of mathematical analysis and its application to messy real-world signals — had calculated what Simons might find especially appealing. She knew how he had made his fortune. She knew the data deluge was real. Maybe, she suggested, the foundation should fund not new experiments but better mechanisms for interpreting existing data. A new research center could "prospect for interesting data sets where people intuit that there's more structure than can be gotten out now, but that aren't so complicated that it's hopeless."
Simons went home to Manhattan and kept mulling. "The more I thought about it, the more I liked it," he said. "And Marilyn liked it." Daubechies had suggested the center be at Duke. The Simonses had a different idea. They asked each other: "Why not do it in-house?"
The Flatiron
The Flatiron Institute opened formally in September 2017, in an eleven-story fin-de-siècle building on the corner of Twenty-first Street and Fifth Avenue. The lobby had that old-but-new look of expensively renovated interiors; every scratch in the building's history had been polished away. Near the entrance hung a Chagall-like painting, "Eve and the Creation of the Universe," by an artist named Aviva Green, whose son happened to be spending the year at the institute as a fellow in astrophysics. "Every day, he walks into the lobby and sees his mother's picture," Simons observed. The detail pleased him.
Downstairs, in the computing core, rows of black metal cages held black metal shelves filled with black server nodes — twinkling lights, protruding multicolored wires, tags dangling with notes the tech staff had written to themselves. The equivalent of six thousand high-end laptops, dedicated to a fraction of the users that a university would serve. Nick Carriero, recruited from Yale, where he had built the university's high-performance computing capabilities for the life sciences, ran the operation alongside Ian Fisk, recruited from CERN. "They're the best of the breed," Simons said.
The institute's structure replicated, in nonprofit form, the architecture that had made Renaissance successful. No new experiments. No wet labs. Instead: bespoke algorithms applied to existing data, developed by first-rate coders in collaboration with university researchers who generated the data elsewhere. Computational biology, computational astrophysics, computational quantum physics — and eventually a fourth division, computational mathematics, which Simons conceived as "glue" binding the others together. Chalkboards lined the hallways. Coffee nooks and communal tuffets encouraged what Simons called sitting around and schmoozing. "An algorithm that's good for spike sorting — some version of it might conceivably be good for star sorting, or for looking at other things in another field."
To lure talent, Simons offered a fifty percent salary increase and the option to work only three days a week, preserving researchers' connections to their home institutions. David Spergel — the astrophysicist from Princeton who had been the runner-up in the university's most recent presidential search, a man who could have gone anywhere — immediately began recruiting. "You get to shape the direction of computational astrophysics," he told prospects. "You will be driving the field if you come here." Of twelve offers to postdoctoral candidates, eight accepted. "We didn't even have a Web page yet!" Spergel said.
Antoine Georges, the French physicist from the Collège de France whom Simons recruited to lead the quantum physics division, had been identified through Simons's "Ocean's Eleven" method: hold a workshop, watch who commands the room. "When he opened his mouth to speak, everyone shut up to listen to what he had to say," Simons recalled. Before agreeing to move to the United States, Georges asked Simons to make a formal commitment to long-term funding. Simons had the Flatiron's board pass a resolution guaranteeing support for at least fifty years. Georges accepted.
By 2019, the institute employed more than two hundred scientists and produced nearly a thousand scientific papers in a single year. MountainSort, one of its early software tools — an algorithm that automates the interpretation of brain-electrode recordings, capable of telling you whether a rat is thinking of turning right or left before it moves — was adopted by research labs worldwide. Chong Xie, a neural engineer at the University of Texas, called it "by far the best spike-sorting tool we have tested," reporting a hundredfold increase in data analysis speed.
The cost? "I originally thought seventy-five million a year," Simons said, "but now I'm thinking it's probably going to be about eighty." Given that Forbes estimated his net worth at $18.5 billion in 2017, the expenditure was, in financial terms, a lark.
"Renaissance was a lot of fun," he said. "And this is fun, too."
The Paradox of Private Science
The Flatiron Institute exists within a paradox that Simons understood but declined to resolve. Private foundations — untaxed, donor-directed, accountable to no public body — represent what Rob Reich, a Stanford political scientist, called "a plutocratic exercise of power that's unaccountable, nontransparent, donor-directed, and generously tax-subsidized. This seems like a very peculiar institutional and organizational form to champion in a democratic society." Edward McCaffery, a tax-policy expert at USC, pointed out that "Democrats like Simons,
Bill Gates, and Warren Buffett might end up giving away all or most of their wealth to charities of their choice, but they and their families still lead lives of great power and privilege, with little tax. And their charities reflect
their values, without necessarily helping ordinary — and taxpaying — citizens."
Simons was unbothered. "I pay a hell of a lot of taxes," he said. "Do I think it's my share? Yes." He defended the Bermuda foundation as no different from any unrealized asset — like shares you never sell. "I wasn't benefitting from it until such time as I would take the money. I think that's a perfectly reasonable thing to do." What went unmentioned was the size of the asset: $8 billion, growing untaxed, controlled by a single family.
When the Paradise Papers investigation revealed the Bermuda entity's scope in 2017, Simons suggested an alternate headline to the reporters: "Brilliant mathematician makes billions and gives it all away to charity." He was not wrong, exactly. But neither were the reporters. The taxes from an eight-billion-dollar fortune could fund a lot of schools.
His candor about wealth inequality, when he chose to exercise it, had a disarming quality. "I believe that the division of wealth we have in the United States has been skewed too much, and I think it would be better if it were less skewed," he said. But then the self-correction: "I'm a beneficiary of all this, but, as for philanthropy and science, I think it's a very good thing, plain and simple. We can go for things that other people can't." A pause. "Originally, all science was supported by philanthropy. Galileo had his patrons."
The Senate investigation into Renaissance's tax practices — the accusation that the firm had used trading structures in the 2000s that effectively lowered its capital-gains taxes by $6.8 billion — cast a longer shadow. Senator Ron Wyden, the ranking Democrat on the Finance Committee, told a reporter: "The law is very clear in this area. Renaissance Technologies abused a tax shelter and pocketed billions from it." Simons maintained that the structures were designed to limit risk, not avoid taxes. "It was a way to limit loss, and it was terrific, and also it gave us quite a lot of leverage," he said. "And when I heard it also would qualify us for long-term capital gains, I said, 'O.K., maybe, but that's not what I care about.'"
Asked how much the arbitration might affect his net worth, he said: "Modestly." Then, quickly: "More than modestly. I mean, it would affect me."
I believe that the division of wealth we have in the United States has been skewed too much, and I think it would be better if it were less skewed.
The Mercer Problem
One thing Simons did not predict was what would happen when he gave brilliant people freedom and resources and then stepped back. At Renaissance, the policy had been resoundingly successful — until it wasn't.
Robert Mercer, the speech-recognition expert whom Simons had recruited in 1993 and eventually elevated to co-CEO, transformed into one of the most divisive figures in American politics during the 2016 election cycle. Mercer, a far-right conservative, spent more than $20 million on political causes, eventually throwing his weight behind
Donald Trump's candidacy. He became likely the single biggest donor to the alt-right, supplying millions to Breitbart, the incendiary website run by Steve Bannon. Simons described Mercer's politics as a transformation that had surprised him. "I've talked to him a few times, but he is just very different from me, and I can't change him," Simons said. Then, with the equanimity of a man who separates output from ideology: "I like him."
But liking wasn't enough when the firm began to fracture. Mercer's growing notoriety was "not so good for morale," Simons said. "One of our very best people had just said he was quitting. Another of the very best people seemed to be on the verge." In October 2017, Simons, as non-executive chairman, encouraged Mercer to resign from his management position. Mercer did so. Simons checked in with the firm's members afterward and was satisfied. "I think I was right," he said.
He had applied his own algorithm — gather data on the state of the system, identify the anomaly threatening its stability, intervene minimally, then verify the result. It was management as signal processing. The irony was rich: the man who "never overrode the model" had to override the human element that no model could account for.
Simons himself contributed $26 million in the 2016 election cycle — to liberal causes. He told people he had always been a Democrat, because of the party's commitment to the poor. He saw no disconnect between paying the least possible in taxes and supporting a party that would like him to pay more. "I'm happy to be one of the rich folks, but I think government ought to do as much as it can to help ordinary folks get on with their lives," he said.
A Nice Theorem on the Boat
Simons owned a $48 million apartment overlooking Central Park, a $65 million private jet (smoking permitted on board; he rented it out when not using it), and a 222-foot yacht called the Archimedes. He was not embarrassed by any of it. He used the yacht to take his old math friends to extraordinary places — French Polynesia, the Mediterranean — and the conversation aboard was as much about Pontryagin classes and the six-dimensional sphere as about the scenery. Jeff Cheeger, a Silver Professor of Mathematics at NYU and one of Simons's closest friends from the Stony Brook years, once developed such an obsessive interest in a topological problem during a Pacific cruise that Tony Phillips found it "annoying. He kept wanting to talk about it."
Simons understood. "I once proved a nice theorem on the boat," he said.
The yacht was named for Archimedes, the ancient Syracusan who famously leapt from his bath crying Eureka — but also the man who, as legend has it, was so absorbed in a geometric diagram that he failed to notice the Roman soldiers who had come to kill him. Simons kept an Archimedes screw on the table next to his ashtray, fiddling with it while he talked. The object connected the playful to the serious, the mechanical to the mathematical, the ancient to the present. It was a toy and a symbol and a working machine, all at once.
His most recent mathematical project, as of 2017, concerned the six-dimensional sphere. "The question is, does there exist a complex structure on the six-dimensional sphere?" he told a reporter. "It's a great problem, it's very old, and no one knows the answer." He was seventy-nine.
High-level mathematics, the conventional wisdom holds, is a young person's game. Practitioners tend to do their best work before forty. Simons — who had won his Veblen Prize at thirty-eight, built a hedge fund at forty, published in the Journal of Topology in his sixties — never entirely accepted this. The mind, like the model, could be trusted to perform if you didn't interfere with it, if you kept feeding it clean data and interesting problems.
The Hundred-Year Bet
In the fall of 2017, the heads of the Flatiron Institute's three divisions sat with Simons at a conference table near his office. All bald men with glasses. The conversation was fast, lightly mocking, and remarkably well-informed. Simons looked in his element.
They were discussing a fourth division. David Spergel suggested computational epidemiology and public health. Leslie Greengard, who had left the directorship of NYU's Courant Institute to run the Flatiron — a man with an M.D. he had never used, who wanted to throw himself into biology — asked whether the field was truly "Flatiron-ready." Simons liked the geosciences instead. He lit up at the complexity of the problems, the connection to climate change, the potential for atmospheric and ocean science. "My guess is there's room to do good work there," he said. The others cautioned that thousands of researchers were already working on climate change. Simons pushed back: "Well, if you added one person who was a real atmospheric guy, eh, that wouldn't hurt." The others assented. For all his affability, he cast the deciding vote.
He had set up the institution to outlast him. The foundation had signed a thirty-five-year lease on the building, with an option to renew for fifteen more. Fifty years of guaranteed funding. An endowment large enough, if the tax laws held, to sustain the enterprise in perpetuity. But humans, he realized, were not machines. "I'm hoping this is going to last a hundred years," he told a visitor. "But I won't see it."
On November 3, 2017, John Grotzinger, a bio-geoscientist from Caltech, came to pitch the Simonses on the geosciences division. He talked about the difficulty of building new telescopes, the problem of data being ignored, the structural divisions of academia that kept geologists from talking to oceanographers. "They will grope their way to a solution probably in the next fifty years," Grotzinger said. "But, if you had it all under one umbrella, I think it could result in a major breakthrough."
Simons smiled. He mentioned the telescope he was funding in the Atacama Desert — about $40 million — to study the cosmic microwave background. "It's going to be beautiful," he said.
The fourth division would be in place by the following September, he decided. Why not eight? Why not Simons University? He had the money. But he insisted four was all he could handle if he wanted both first-class work and a collaborative atmosphere. He needed to manage it all, he said, with his "light touch."
The Flatiron was, in a sense, the final expression of an algorithm Simons had been refining since Stony Brook: hire brilliant people, give them extraordinary resources, remove every excuse for not producing, and then — this was the hard part, the part most people got wrong — step back. Let the model run.
"Working for Jim," Peter Brown once recalled, "you had the feeling that you had better produce, because he had pretty much removed every excuse for not producing."
On May 10, 2024, James Harris Simons died in New York City, at the age of eighty-six. His wife Marilyn, three children, five grandchildren, and a great-grandchild survived him. The Flatiron Institute was producing nearly a thousand scientific papers a year. The Medallion Fund had never had a losing year. The Simons Foundation had given away more than $6 billion. The telescope in the Atacama Desert — 16,500 feet above sea level, in one of the driest places on Earth — was scanning the sky for the faintest echoes of the beginning of everything.
Somewhere in that data, patterns no one has yet detected are waiting for the right algorithm to find them.
