Head of Data at AIOS — Remote, $150k-$300k/yr inc equity

ABOUT AIOS AIOS is building the world’s first full-stack AI doctor. We’re at $350M ARR, growing from $10M/yr 12 months ago. We’re the world’s fastest growing AI doctor. We’re faithfully serving >150k/mo patients via Bolt Pharmacy, our main UK brand. We’re profitable. Our strategy exists at the intersection of two strong theses: 1. The AI doctor that wins will get to escape velocity using GLP-1s, the fastest growing consumer product in history. 2. The $2T European healthcare market is overlooked by the most talented builders. Our master plan: - Step 0 → $100M/yr by end of 2025: We went from $10M to $100M in 6 months serving the UK GLP-1 market.

• Step 1 → $1B ARR by end of 2026: Over the last 12 months we've grown from 3k to 150k UK active GLP-1 patients.

• Step 2 → $10B ARR by end of 2028: Blitzscale Europe. We’ll be Europe’s largest GLP-1 provider.
• Step 3 → $100B/yr by end of 2031: Get regulatory approval across Europe for our Full Autonomous Prescribing (FAP) system. Win contracts at scale with European payers to mass replace human labor.

• Step 4 → $1T/yr by end of 2035: With one line of code and zero human time, you can use AIOS to treat any patient globally with any medication. In so doing, we’ll become the world’s first trillion-dollar healthcare company. We’re a young, founder-led company. This is still Day 1 and all our work is ahead of us.

• Our dbt layer is clean, documented, and designed to scale.
• Every core company metric has a precise, canonical definition.
• Leaders can confidently use Hex AI to explore trusted data and answer important business questions.
• Engineering and Data have clear contracts for how product data enters the warehouse.
• We’re building the evidence layer required to speak credibly with regulators about our clinical and AI systems.

• Architecture: You’ll define how our data platform should evolve as AIOS grows by orders of magnitude.

• dbt: You’ll establish clear standards for staging, intermediate, and marts models. You’ll define how new models are proposed, designed, reviewed, tested, documented, deployed, and eventually deprecated.
• Metrics: You’ll own the definitions behind the metrics that run AIOS across growth, activation, retention, revenue, product, clinical operations, CX, and Ops.

• Hex AI: You’ll make Hex AI the best possible interface for understanding the business. Leaders should be able to ask important questions against clean, intuitive models without recreating business logic in every dashboard.
• Performance & Reliability: You’ll work with the team to keep our warehouse and pipelines fast, reliable, and cost-efficient as data volume and usage grow.

• Experimentation: You’ll establish how AIOS designs, instruments, and evaluates experiments. You’ll ensure results are statistically sound, prevent teams from drawing confident conclusions from weak evidence, and identify when specialist Data Science support is needed.
• Engineering: You’ll partner closely with Engineering on source schemas, product events, breaking changes, data contracts, and backfills.

• Business Partner: You’ll become a key partner to every functional lead. You’ll understand their domain deeply, challenge weak KPIs, and help them find the measurements that actually drive better decisions.
• Build the Team: You’ll lead our existing data team, hire an additional Data Engineer once you’re onboarded, and continue growing the function based on what the company needs most.
• Regulatory Evidence: You’ll start designing the data foundations required to demonstrate the quality, safety, and performance of our clinical and AI systems.

• Vendors: You’ll own our relationships with Hex and other important data vendors. You’ll lead escalations, push for reliable products, evaluate whether tools still serve us, and negotiate as AIOS scales.
• Systems: You’ll move important business logic out of ad hoc dashboards and into governed models.

• SQL & dbt: You’re deeply fluent in SQL and dbt.

• Data Architecture: You’ve helped design and operate a modern data platform spanning ingestion, a cloud warehouse, transformation, reporting, and monitoring. You understand how each layer should fit together.
• Data Engineering: You understand how production data systems behave beyond the modeling layer.

• Metrics: You can turn an ambiguous business goal into a precise metric.

• AI-Native: You use AI heavily in your own work and have strong instincts for making AI-assisted analysis more reliable, contextual, and useful.
• Judgement: You know which logic belongs in dbt, which belongs in Hex, which requests should become canonical models, and which requests should not be built at all.
• Leadership: You set a crisp direction and quality bar while giving strong people room to execute.

• Player-Coach: You’re excited to primarily operate at the managerial and system level, but you haven’t lost the ability or willingness to inspect the actual work. You won’t hide behind your team.
• Stakeholders: You challenge senior leaders without hesitation when a KPI is misleading or poorly defined, then work with them to build a measure that drives better decisions.
• Reliability: You’ve established monitoring, data-quality checks, ownership, and incident processes for business-critical data.

• Ownership: When a model is wrong, a dashboard is stale, or a vendor is failing us, you take responsibility for reaching the outcome. You do not stop at identifying which system or person is technically at fault. NICE TO HAVE - Scale: You’ve helped a data function keep pace with a company experiencing extreme growth.

• Redshift: You’ve operated Redshift or a similar cloud data warehouse at meaningful scale.
• Hex: You’ve used Hex or another modern collaborative analytics platform and understand how to enable self-service without creating hundreds of competing truths.
• Consumer Metrics: You’ve worked deeply with acquisition, activation, retention, churn, revenue, cohorts, and unit economics in a consumer or subscription business.
• Multi-Market: You’ve built data systems supporting multiple brands, countries, and/or products without creating a separate data universe for each one.
• Regulatory Evidence: You’ve thought about how product and operational data can become traceable, auditable evidence for regulators or other high-stakes external stakeholders.
• Talent: You have a strong nose for exceptional data talent and know how to build a lean, high-performing team.
• Figure It Out: You can move from a broken executive dashboard, to a dbt architecture discussion, to a difficult vendor escalation, to a KPI debate with a functional lead while making progress on all four.

• A maniacal sense of urgency: We execute at an intensity that most people think is impossible. Speed is critical and we need things done yesterday. We all work very hard and in such a competitive world there really is no other way to win. 7. Enduring frugality: We are frugal. We hate being wasteful and we are anti-luxury.

• Keep your head down: We’re boring people doing exciting work. We don’t chase short-term status — we ignore short-term dopamine hits and focus on what matters. Outsiders will underestimate us and we revel in that. 10. The power of focus: We live in a world of power laws and we cannot overestimate the unimportance of practically everything.

• ## Compensation

• Healthcare: comprehensive medical insurance (if appropriate) - Vacation: PTO with a yearly minimum (≥2wks/yr + local national holidays) - Remote: our team is fully distributed across the world and functions fully remotely - Personal development: budget for books, courses, coaching ($1200/yr) - Personal wellness: budget for gym, health apps ($1200/yr) - Coaching: free biweekly health coaching - Equipment: Macbook & work-from-home equipment provided as needed - What are we missing?

• Highlight concrete examples where you built or revamped a dbt layer and the business impact it had.
• Prepare a short case study showing how you defined a metric, discovered a flaw, and aligned stakeholders on a corrected definition.
• Bring a portfolio of dashboards or analytics projects, especially if they use Hex, Looker, or similar self‑serve tools.
• Expect technical interview questions on data pipeline design, schema evolution, and handling data quality incidents.
• Emphasize any experience with regulated data or healthcare compliance, as AIOS works closely with regulators.
• When negotiating, factor in equity potential given AIOS’s rapid growth trajectory and the strategic importance of data.
• Watch for vague answers about data governance; the interviewers will probe your methodology for metric definition and documentation.