Head of Applied AI & Trading Systems (Iron Man Track)

About this role

The Gist Deeter Analytics is a private investment firm managing approximately $500M across public markets, alternatives, and private investments. We are small, profitable, and aggressive. We don’t have committees. We have capital, judgment, and a need for speed. We are hiring a technical builder to sit directly beside the CIO and architect the firm’s intelligence layer — the system that determines how we see the market .

This is not a quant role. This is not a reporting role. This is not a research-for-research’s-sake role. This is a Human-in-the-Loop AI role : building the Iron Man suit — an exoskeleton that allows a human trader to process 100× more information without losing intuition, discretion, or speed. This role sits at the center of our trading advantage. The Problem Markets are noisy. Alpha comes from synthesis. We already have access to the data.

The bottleneck is human bandwidth . Too much time is spent: Refreshing feeds Reading things that don’t matter Manually stitching together signal across sources Latency kills insight. Insight kills latency. The Mission Build the nervous system of the firm. You will own the entire loop: Ingestion → LLM synthesis → Trader decision Your mandate is simple and brutal: Reduce time-to-insight across the entire trading operation.

If you surface a signal 10 minutes faster than the street, we win. If you automate away four hours of reading, we double our capacity. What You Will Own 1. Information Pipelines (Kill the “F5” Key) 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. 2. AI-Augmented Research (A Live Analyst on the Desk) 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. Example: “Summarize the bear case from the last three earnings calls.” You will also create tools for fast discretionary back-testing: “How did this asset behave during the last three macro shocks of this type?” 3.