About

About the company Core 11 is a private investment firm that acquires companies in fragmented markets including distribution, industrial automation, field services, and data-managed services, embedding AI and analytics from day one to drive efficiency, consolidation, and better customer outcomes. We target sectors with low digital maturity but high scale potential, creating value through data-driven operational excellence. By building AI/ML tools that improve core operations within platform companies, we establish a foundation for market roll-ups and long-term competitive advantage. About the role You will be a core member of a lean, high-velocity team, and specifically responsible for encoding the private equity discovery and decision process in a records- and data-centric architecture to support systematic and hypothesis driven thinking. You will design and build workflows that apply modern software and automation best practices to the open-ended and more traditionally human-driven private equity investment process. You will use this system to design and perform experiments to develop machine-driven insights in this space. What you’ll do * Design and implement cloud-based data architectures which integrate versioned inputs across a multitude of sources, and which support an open-ended R&D dev environment. * Formulate testable hypotheses; design and run experiments on real data; analyze results statistically to quantify forecasts for a variety of outputs (revenue, unit economics, risk, operational interventions, investment returns) * Remain in tight communication and coordination with a small team, ensuring your work is delivering impact, developing solutions to emergent problems, and documenting your results as we accumulate reusable IP. What you bring * BS in Math, Computer Science, or related field. Fluency with modern machine learning, data structures and algorithms. Professional or Project-based experience with contemporary cloud-based software hygiene (revision control and versioning, dependency management, security and permissioning, test automation, etc). * Aggressively curious and skilled in the use of modern LLM based tools to leverage yourself as a software developer and quant researcher. You are proactively developing best practices and exploring new applications of this emergent tool set. * High degree of mission empathy; ability to stay abreast of the evolving priorities of a small, interdisciplinary team and adjust accordingly. Ability to unblock yourself and others, develop quick prototypes to test ideas or deliver insights, while also thinking long term about which systems will need further polish. * Design-first approach to software system development, blending an algorithmic mindset with the creativity required to deliver workflows that are flexible and extendable enough to support open ended research. A pragmatic mindset and a bias for simple, testable solutions. * Statistical intuition and mathematical abilities needed to design, perform and evaluate rigorous and effective computational experiments. * Clear and concise thinking and communication; appropriate precision in your written and spoken manner. * Broad curiosity about the business and financial elements of the investment process; excited to work alongside a deeply experienced senior team and to integrate what you learn into your technical work.