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Tower Research hired an ex-equities portfolio manager to manage its risk. 4 hours ago A lot of people want to work in an electronic trading firm. Many of them are willing to work in a non-investment role to do so, but it's a rarer case for someone with a history in the front office to join the middle. Pierre Danilowiez, formerly of SocGen, has done just that to work for Tower Research. Danilowiez joined the firm's Amsterdam office as a senior risk manager. He was most recently head of investments for Arbra, a multi-family office. His LinkedIn states that the role involved asset allocation for the firm's various investment teams, and the development of the firm's risk framework, which would lend itself well to a pure risk role. His role also involved "directly managing $100M+ multi-asset portfolios," which seems much more front-office oriented. Before that, he was a trader for 15 years. He spent five years as a portfolio manager at asset manager Key Capital Partners, where he claims to have managed a €30m AUM strategy in equities. He also spent a decade at SocGen, where he was a VP in equity derivatives trading. Danilowiez is a Grande École mathematics and engineering graduate. French-educated equity derivatives specialists are highly sought after right now; In London, Optiver hired Barclays MD Arnaud Heckenroth as head of exotics business development, suggesting that there's further room for algo firms to expand in the already competitive world of equity derivatives. Tower seems to prefer hiring support staff to traders right now. In 2025 accounts for its UK entity filed with Companies House this week, the firm revealed that headcount in its 'trading' unit fell by 18 while headcount in 'support/management' rose by seven. Tower did not respond to a request for comment on whether it made any cuts, or whether any staff were reassigned from a trading role into support. Have a confidential story, tip, or comment you'd like to share? Contact: WhatsApp: http://wa.me/442079977910 (+44 20 7997 7910), Telegram: @AlexMcMurray, Signal: @AlexMcMurrayEFC.88 Click here to fill in our anonymous form, or email [email protected]. Bear with us if you leave a comment at the bottom of this article: comments are moderated intermittently by human beings. Sometimes these humans might be asleep, or away from their desks, so it may take a while for your comment to appear. You must take sole responsibility for comments you post on this site. We will take reasonable steps to weed out anything that we consider to be offensive or inappropriate. The essential daily roundup of news and analysis read by everyone from senior bankers and traders to new recruits. Boost your career. Find thousands of job opportunities by signing up to eFinancialCareers today. Top Articles

The American Baby Company, a West  Palm Beach-based fertility startup, has raised a $4 million seed round. The round was led by Wormhole Capital and Tower

Poker AI turns to trading. Three former DeepMind researchers taught an AI to beat professional poker players. Now the same approach trades stocks. Their Prague lab, EquiLibre Technologies, reached a $500 million valuation after a Series A led by Creandum, and the early results look strong. Key takeaways. * EquiLibre Technologies, founded by three ex-DeepMind researchers, reached a $500 million valuation after a Series A led by Creandum, the firm's largest single investment ever. * Working with quant firm Tower Research Capital, EquiLibre's agents trade billions daily across the S&P 500 and Nasdaq and claim zero negative months since inception. * The founders came from the DeepStack poker project and apply reinforcement learning, where markets offer one simple reward signal: profit. Why poker and markets rhyme. Both games reward the same kind of learning. Reinforcement learning trains a model through rewards, letting it improve by trial and error. Poker and trading both suit that method well, and trading has one clean scorecard. "The nice thing about trading and markets is that the scoring is super simple: how much money did the agent make?" said Martin Schmid, EquiLibre's CEO. This is not play money. Partnered with Tower Research Capital, EquiLibre's algorithms trade billions in daily volume across the S&P 500 and Nasdaq. The startup says its agents have done well since launching on crypto in 2025 and now on stock exchanges, claiming "a perfect record of zero negative months since inception." Academic work on reinforcement learning for quantitative finance has pointed at this potential for years. A lab first, not a fund. The money came fast. Creandum led the round, and vice president Cameron Sellers confirmed it was the largest single investment the firm "has ever made in one go into a company." He framed the appeal in scale. "The potential total addressable market of trading in the financial markets is one of the biggest on earth, and there are countless funds over the years that have generated quantums of profit that make most venture-backed successes look small," Sellers said. He also noted that EquiLibre calls itself "a lab first, not a finance firm." The founders back that identity. Schmid, along with CTO Rudolf Kadlec and CSO Matej Moravcik, do not come from finance, and Schmid says that is not the draw. "I'm not doing this because I'm excited about making markets efficient. I'm doing this because we are all excited about building new things that have never been built before, and this is a lot of fun to build," he said. The trio met as visiting PhD students at DeepMind's Edmonton office, which Alphabet closed in 2023. There they built DeepStack, the first AI to beat pros at no-limit Texas hold'em. Their advisory board includes Rich Sutton, who won the 2024 Turing Award for his reinforcement learning work. Money, chips, and rivals. The funding history climbs steeply. A pre-seed came from Credo, an early backer of ElevenLabs and UiPath. A $10 million seed led by Blossom Capital valued the company at $140 million. The Series A now pegs it at $500 million. The team of 25 plans to scale its compute next, aiming to bring online one of the largest clusters in Central and Eastern Europe. Prague helps, Schmid says. "It's much easier to keep the good people here, because there's not a new sexy AI thing happening every two months." Competition is real. Trading giant Jane Street says it already uses reinforcement learning with large language models, "or whatever else we need to train good models," and claims "tens of thousands of high-end GPUs." EquiLibre wants to squeeze more out of far fewer chips and "get more from less," Schmid said. He is not treating it as a fight to the death. "This is not a winner-takes-all market." A trend investors keep chasing. DeepMind alumni have become a favorite bet. Money keeps flowing to elite researchers starting labs outside the big incumbents, from London to Prague, and nine-figure and ten-figure rounds for ex-DeepMind teams now land regularly. The founders describe trading as a field where the market delivers its verdict every millisecond, with a research team drawn from DeepMind, Google, and top trading houses. That framing, technology as the entire game, is exactly what pulls big checks toward the crowded AI startup market. Quant funds are moving the same direction. Machine learning is replacing older statistical methods across the industry, and reinforcement learning has gone from fringe to standard in a few short years. "When we started, people were skeptical," Schmid said, though the mood has flipped. "Because we started four years back, we believe we are ahead." Whether the head start holds is the open question, and the report that revealed the round makes clear that deep-pocketed rivals are training the same techniques on far more hardware.