Applied AI Strategist - Market Intelligence (Health) in London

This is not “market research.” No 60‑page decks. No generic “digital health is big” observations. This is a continuous loop: market → signal → implication → decision → shipped product. Your job is to keep Terra’s roadmap and GTM pointed at the sharpest opportunities across AI × health, using live conversations with users and near‑users, Terra’s own data and product surfaces, and the messy, high‑resolution context everyone else ignores.

What you’ll do

• Obsess over the people building on health data and AI. Talk to founders, PMs, engineers, ops people, and researchers building on top of wearables, labs, and longitudinal health data. Extract what they’re actually trying to achieve, where they’re stuck, and what they’d pay for if it existed.
• Turn chaos into sharp segments. Break the world into concrete, actionable segments like “AI assistants for metabolic health decisions” or “B2B platforms embedding Terra‑like health memory.” For each one: what they need from Terra, how big it is, and how fast we can move.
• Spot early product patterns from Terra’s own signals. Read our usage, logs, support threads, builder questions, and integration patterns. Turn that into: “these are the workflows emerging on Terra; here’s the product that would make them 10x easier.”
• Live where our builders live. Hang out in the places our users actually are: GitHub, AI forums, communities, niche health and bio circles, Telegram / Discord, X threads. Pull out early weirdness and translate it into “here’s a bet we should place.”
• Feed the team with decision‑grade direction. For product: what to build, in what order, and which segments to explicitly ignore for now. For GTM: which users and use‑cases to prioritize this quarter, and what language will actually land.
• Ship clear, small artifacts. Short memos, briefs, Looms-whatever works-as long as it’s clear. One screen, one idea, one decision.

How you think

You probably recognize yourself in most of this: You operate at street‑level resolution: real users, real tools, real workflows—not abstract “AI will change healthcare” slides. You like being early more than being universally agreed with. You’re comfortable saying “this is my best read with incomplete data, here’s the cost of being wrong.” You think in systems: products, data, incentives, distribution. You are allergic to analysis that doesn’t change what people do. You are AI‑native: you reach for Perplexity / GPT / agents the way others reach for spreadsheets. You instinctively ask “how would an AI use this data?” and “what does this unlock for AI?” when you see a new product idea.

What we care about

We don’t care about “years of experience.” We care about how you see and how you move. You might have run product/market research or strategy at a startup, fund, or product org; built or worked around AI products, agents, or pipelines—and can show us your prompts, flows, or internal tools; done real work around health, data, or AI products (or can prove you climbed the curve fast); examples where your work directly changed a roadmap, pricing, positioning, or a go/no‑go decision. You definitely move fast and don’t hide behind “we need more data”; can show written work that is brutally clear and directly actionable; are comfortable sitting close to founders and saying “I disagree, here’s why” when your read says so.