Deeter Analytics

Deeter Analytics At Deeter Analytics, we’re building something that doesn’t get built twice in a generation. Our goal is to create a fundamental trading model as capable as today’s most advanced AI systems — but applied to global markets. Not incremental signals or isolated strategies, but a system that can continuously interpret, learn from, and act on the evolving state of the world. We train on large-scale, real-time social data — capturing how narratives form, how sentiment propagates, and how collective behavior drives markets. This requires operating at the frontier of data infrastructure, model design, and compute, all tightly integrated into a single system. You’ll work alongside a small group of elite traders, engineers and AI researchers, in an environment defined by speed and ownership. We run experiments continuously. Ideas move from concept to production in hours. And the feedback loop is immediate — measured directly in live performance. About the role You will build systems where AI agents do most of the implementation, and your role is to define, structure, and validate what gets built. This is closer to operating a high-throughput production system than writing code line-by-line. We prefer systems that scale through better specifications and feedback loops, not manual implementation. What you’ll work on ● Defining systems through clear, executable specifications ● Designing behavioral scenarios and acceptance tests that validate outcomes ● Running tight loops: spec → agent execution → validation → iteration ● Structuring work so agents converge quickly and reliably ● Shipping systems into production with monitoring, rollback strategies, and fast iteration under real constraints What we’re looking for We’re looking for people who can turn ambiguous problems into systems that work, using AI as a primary building tool. Strong signals: ● You have shipped production systems built largely with AI agents ● You think in terms of behavior and outcomes, not implementation details ● You can write precise specifications that machines can execute ● You design validation through scenarios/adversarial cases/black-box testing ● You run fast iteration loops and know how to drive systems toward convergence ● You are comfortable operating at scale large contexts/high token usage/parallel runs ● You take ownership of production outcomes, not just development Bonus signals: ● Experience building or contributing to agent tooling or workflows ● Public work that clearly shows AI-assisted development processes ● Experience designing evaluation systems that are hard to game ● Experience operating as a high-leverage individual or in very small teams ● Strong written communication — clear, structured, and unambiguous

Deeter Analytics At Deeter Analytics, we’re building something that doesn’t get built twice in a generation. Our goal is to create a fundamental trading model as capable as today’s most advanced AI systems — but applied to global markets. Not incremental signals or isolated strategies, but a system that can continuously interpret, learn from, and act on the evolving state of the world. We train on large-scale, real-time social data — capturing how narratives form, how sentiment propagates, and how collective behavior drives markets. This requires operating at the frontier of data infrastructure, model design, and compute, all tightly integrated into a single system. You’ll work alongside a small group of elite engineers, AI researchers, and traders, in an environment defined by speed and ownership. We run experiments continuously. Ideas move from concept to production in hours. And the feedback loop is immediate — measured directly in live performance. About the role You will build and optimize the systems that turn data and compute into model capability. This role sits at the intersection of distributed systems, GPU infrastructure, and model training — ensuring that both our in-house models and state-of-the-art external models can be trained efficiently at scale. We prefer systems that maximize learning per unit of compute, not just systems that run. What you’ll work on ● Designing and operating distributed training systems on GPU infrastructure ● Optimizing GPU utilization, throughput, and training efficiency ● Translating model requirements into efficient system configurations ● Improving training speed, cost efficiency, and reliability ● Debugging failures in high-cost, high-pressure training environments What we’re looking for We’re looking for people who understand how systems behave under real constraints — and know how to push them to perform. Strong signals: ● You have run or significantly contributed to large-scale training workloads or compute-intensive systems ● You have a strong understanding of distributed systems in practice, including public cloud environments like AWS ● You understand how infrastructure behaves beneath the abstraction: ○ networking constraints ○ GPU/CPU utilization ○ memory and I/O bottlenecks ○ hardware limits at scale ● You can reason about how systems can be tuned for more efficient training and resource usage ● You have debugged systems where failures were non-trivial and costly ● You move quickly, identify bottlenecks, and eliminate them without being asked Bonus signals: ● Experience optimizing systems where small efficiency gains had large downstream impact ● Experience working under strict compute or cost constraints ● Experience debugging distributed or asynchronous systems with non-obvious failure modes ● You use AI tools to accelerate debugging, development, and iteration ● You care about building systems that are measurably efficient, not just functional

• stabilize and rebuild the talent function • architect the day-to-day operations of the Family Office • ensure the Principal’s time is leveraged for maximum impact

• Own the coherence and simplicity of all internal systems • Manage engineering roadmap • Create momentum and deliver internal tools quickly • Lead through clarity and architectural direction • Collaborate closely with the Founder and senior leaders

• Design, build, and maintain data pipelines for unique and multimodal datasets. • Train and evaluate frontier-scale models; own the loop from idea to prototype to production. • Work shoulder-to-shoulder with researchers to discover new methods.

• Formulate and pursue original research agendas (reasoning, tool connectivity, robustness, alignment, data/compute efficiency). • Follow Ideas to PoC to MVP to training to validation, owning all steps of the process with deep collaboration with Research Engineers (see other open role). • Build rigorous evaluation suites through simulated environments and real time evaluation. • Prototype fast with real data; partner with Research Engineers to take promising ideas to production.

• You will design and maintain automated pipelines that ingest, clean, and normalize: • News, filings, earnings calls, macro releases • Social and sentiment data • Alternative and proprietary datasets • Your job is to replace manual refresh workflows with push-based alerts that surface only what matters — mapped directly to: • Watchlists • Live positions • Risk exposure • Reliability matters. Latency matters. Silence matters. • You will deploy LLM-powered systems to summarize, extract, compare, and reason over: • 10-Ks, 10-Qs, earnings calls, central bank minutes • Sell-side research and internal notes • You will build “chat with our data” tools that allow traders to query proprietary research in natural language. • You will also create tools for fast discretionary back-testing: • How did this asset behave during the last three macro shocks of this type? • You will build the filters that decide what breaks through. • Sentiment and relevance scoring • Entity recognition that maps events to exposure • Dashboards that surface regimes, anomalies, and dislocations — not vanity metrics • If something matters, it should scream. If it doesn’t, it should disappear. • You own the compute layer that runs the intelligence system. • Cloud and/or local GPU infrastructure • Vector databases and retrieval systems • Data-privacy-first architectures (local models where required) • You choose the architecture. You ship what runs fastest and breaks least. Our proprietary data and strategies do not leak. Ever.

Head of Research About Deeter Analytics Deeter Analytics is a privately held investment research and trading firm managing approximately ~$500M across public markets, alternatives, and private investments. We operate with a small, senior, high-performance team within a deeply entrepreneurial culture. We value autonomy, judgment, clarity, and technical rigor. We hire very few people, expect a great deal from them, and invest heavily in long-term performance and trust. This environment suits sharp, self-directed thinkers who can hold ambiguity, exercise independent judgment, and translate complex inputs into clear action. Role Overview The Mandate: The Principal operates in fast-moving, highly competitive global markets where asymmetric information and early insight define success. We require a research leader who functions as a force multiplier—someone who transforms complexity into clarity and conviction into profitable action. You are the engine that converts raw information into durable advantage. We are looking for a strategic thinker and relentless operator who sees what others miss and moves before consensus forms. The Requirement: Intellectual and Strategic Mastery

Trader & Executer The Firm We operate a private investment office managing a concentrated portfolio of liquid assets. We are a small, discreet team that prioritizes agility and intellectual honesty over traditional corporate hierarchy. This is a role for a high-ceiling individual who prefers a quiet, high-stakes environment over the noise of a large institution. The Role This position is focused on the precision execution of trades and the real-time monitoring of portfolio risk. You will not be a "cog in a machine"; you will be the primary support to the Principal, responsible for: Execution: Handle daily trade execution across various asset classes (equities, derivatives, and potentially commodities). Quantitative Support: Work closely with the Principal to analyze market themes and assist in developing data-driven trading strategies. Risk Oversight: Maintaining a constant pulse on exposure and ensuring adherence to firm mandates. The Profile We do not require a traditional finance background. In fact, we are specifically looking for "raw" talent—individuals who have a natural, perhaps non-traditional, history of managing risk and making high-pressure decisions. Decision Science: You have a demonstrated ability to think in bets. You understand expected value and can make rapid-fire calculations when the environment is shifting. Calculated Temperament: You possess the rare ability to remain clinical and disciplined when volatility increases. Inherent Sharpness: You are someone who "gets it" quickly. We value a track record of winning in competitive, high-stakes environments—whatever those may be. Integrity: Absolute discretion is the baseline. You will be operating in a private, sensitive capacity where trust is the primary currency. Why Join Us? This is an apprenticeship-style role. You will be sitting at the center of the decision-making process, gaining a level of transparency into global macro strategy and capital management that is impossible to find at a bulge-bracket bank or a high-volume prop shop.