Top Tech Startups in Earth in 2026

The D. E. Shaw group is trusted by investors across the world to manage their assets by seeking the optimal balance of risk and reward. While we’re known as a pioneer in quantitative investing, we also have considerable expertise in areas that involve fundamental analysis or portfolio manager discretion. We use a combination of quantitative and qualitative tools to uncover independent, hard-to-find sources of return across global public and private markets. Founded in 1988 over a small bookstore in downtown New York City, the D. E. Shaw group began with six employees and $28 million in capital and quickly became a pioneer in computational finance. In the early days of exposed pipes and extension cords, tripping on a cable could take out our whole trading system. Today, the firm has more than 2,500 people around the globe and an institutional-grade (and trip-proof) infrastructure, but we still value creativity, entrepreneurship, and the spirit of discovery. If you’re an intellectually adventurous person who loves to collaborate on challenging and rewarding projects, we encourage you to apply. Visit our Careers page at deshaw.com/careers to learn more.

Aurora Genesis is an early-stage startup building Aurora Origins, a consumer platform that models complex personal data and turns it into something people can explore and act on. We're pre-seed and founder-led, working on hard problems in data modeling, systems design, and making complex information legible to people

Your Trusted Partner in Consulting and Talent Acquisition Solutions

AI capabilities are spreading across companies faster than anyone can keep track of them. Teams are creating prompts, skills, instructions, agents, workflows, and tools across different models, repositories, and platforms, often with no shared view of what exists or which version people should actually use. Commonset gives organizations one place to see what AI capabilities exist, who owns them, where they came from, what changed, and which ones the organization actually trusts and uses. We’re building the management layer between the models and the organization: model-agnostic infrastructure for discovering, governing, distributing, and reusing AI capabilities without tying them to a single vendor. We’re early, moving quickly, and looking for people who want to help shape both the product and the company.