Data Operations Manager, Scientific Data

Description: Own the operations that turn Axiom’s scientific plans into massive, high-quality experimental datasets that power frontier agents and models to predict human drug outcomes with insane accuracy. About Axiom: Axiom’s mission is to eliminate unexpected drug toxicity and unlock an abundance of ultra safe medicines. We are starting with the liver, where toxicity remains a leading cause of drug failure. Our high-throughput human liver safety platform combines advanced human cell systems with imaging, transcriptomics, mass spectrometry, and drug metabolism measurements. Our AI agents integrate these data with chemical structure, human exposure, and thousands of clinical reference compounds to predict whether a drug will be toxic in humans, why, and how to make it safer. We work with seven of the world’s top twenty pharmaceutical companies to design safety into molecules from the earliest stages. This applied work feeds directly into our partnerships with leading frontier AI labs, turning real discovery challenges and experimental feedback loops into scientific skill trees and reinforcement learning environments that train increasingly superhuman scientists. We then deploy these frontier models to make cancer therapies safer, unlock treatments for chronic diseases that demand exceptional safety, revive promising drugs abandoned because of toxicity, and much more. Our ultimate ambition is to build a superhuman AI agent that predicts how a drug will behave across all major human organ systems before the first patient receives it. With insanely accurate safety predictions, we aim to enable rapid, high-throughput testing of novel drugs in humans with zero risk of toxicity. This is the key to unlocking an abundance of ultra safe, effective medicines. What you will do: - Own operational delivery of Axiom’s scientific data programs, translating research and customer requirements into clear plans, milestones, quality standards, budgets, and deliverables. - Coordinate data generation across internal teams and partner laboratories, managing capacity, dependencies, timelines, and handoffs from experimental planning through validated data delivery. - Manage compound sourcing, purchasing, sample manifests, inventory, international shipping, and customs documentation so laboratories have the right materials when they need them. - Build and manage laboratory and supplier partnerships, establishing clear specifications, delivery commitments, acceptance criteria, and processes for resolving failures. - Protect data integrity by reconciling compound identities, barcodes, sample histories, experimental metadata, and incoming results, working with scientists and data engineers to resolve discrepancies before downstream use. - Build scalable operating systems using trackers, dashboards, SOPs, alerts, and AI agents to automate coordination, surface risks early, and reduce manual follow-up. - Keep pharmaceutical customers, AI research partners, laboratories, and internal teams aligned through clear communication, timely escalation, and reliable delivery. - Manage SOWs, purchase orders, invoices, and project budgets, tracking spending against progress and identifying opportunities to improve cost and turnaround. - Measure and improve throughput, delivery reliability, and data quality, ensuring each program strengthens the operations behind Axiom’s drug discovery, Translate, and AI training workflows. What we look for: - Exceptional execution and end-to-end ownership. You anticipate blockers, manage competing priorities, and deliver complex programs across multiple teams and external partners. - Exacting attention to detail. You catch inconsistencies in samples, identifiers, datasets, schedules, and budgets before they become costly downstream failures. - Strong analytical and technical judgment. You use data, spreadsheets, SQL, Python, or other tools to investigate problems and make sound operational decisions. - A track record of building scalable processes. You turn recurring problems into clear workflows, automated checks, and systems that improve speed and reliability. - The ability to translate nuanced scientific and research requirements into concrete specifications, quality standards, and deliverables. - Strong partner management and communication skills. You build trust, set clear expectations, navigate difficult conversations, and keep customers, researchers, and vendors aligned under pressure. - Comfort with ambiguity and changing priorities, supported by experience in operations, program management, consulting, or similarly demanding roles. - Curiosity about biology, chemistry, drug discovery, and AI, with an interest in how high-quality experimental data improves models and scientific agents. - A habit of using AI tools and automation to improve your own work, with the judgment to verify outputs and maintain accountability. Technical skills we value: - Data management and analysis using spreadsheets, SQL, Python, dashboards, and automated reconciliation and validation tools. - Program planning, dependency tracking, capacity planning, risk management, and quantitative process improvement. - Workflow automation and AI agents for tracking deliverables, reconciling records, coordinating handoffs, and surfacing exceptions. - Vendor and commercial operations, including SOWs, purchase orders, invoices, budgets, and performance tracking. - Compound procurement, supplier coordination, inventory management, international shipping, and customs documentation. - Scientific operations, including experiment scheduling, sample tracking, compound identity management, and laboratory data delivery. - Clear SOPs, documentation, acceptance criteria, and escalation processes that keep internal teams and external partners aligned. - Prior biotech or laboratory experience is helpful but not required.