Data Operations Manager, Scientific Data

Axiom • South San Francisco, CA

9h

About The Position

Own the operations that turn Axiom’s scientific plans into high-quality experimental datasets used to train frontier agents and models that predict human drug outcomes. The role oversees operational delivery of scientific data programs, translating research and customer requirements into plans, milestones, quality standards, budgets, and deliverables. It coordinates data generation across internal teams and partner laboratories, manages materials and supplier relationships, protects data integrity, and builds scalable operating systems and automation. The position also keeps customers, research partners, laboratories, and internal teams aligned; manages commercial and budget processes; and improves throughput, delivery reliability, and data quality across Axiom’s drug discovery and AI training workflows.

Requirements

• Exceptional execution and end-to-end ownership, including anticipating blockers, managing competing priorities, and delivering complex programs across teams and external partners.
• Exacting attention to detail when handling samples, identifiers, datasets, schedules, and budgets.
• Strong analytical and technical judgment, using data and tools such as spreadsheets, SQL, or Python to investigate problems and make operational decisions.
• Experience building scalable processes, workflows, automated checks, and systems that improve speed and reliability.
• Ability to translate nuanced scientific and research requirements into concrete specifications, quality standards, and deliverables.
• Strong partner management and communication skills, including setting expectations, navigating difficult conversations, and keeping stakeholders 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, and interest in how experimental data improves models and scientific agents.
• Habit of using AI tools and automation to improve work, with judgment to verify outputs and maintain accountability.
• Skills in program planning, dependency and capacity tracking, risk management, and quantitative process improvement.
• Skills in vendor and commercial operations, including SOWs, purchase orders, invoices, budgets, and performance tracking.
• Skills in compound procurement, supplier coordination, inventory management, international shipping, and customs documentation.
• Skills in scientific operations, including experiment scheduling, sample tracking, compound identity management, and laboratory data delivery.
• Ability to create clear SOPs, documentation, acceptance criteria, and escalation processes.

Nice To Haves

• Prior biotech or laboratory experience is helpful but not required.

Responsibilities

• Own operational delivery of scientific data programs, translating research and customer requirements into 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.
• Build and manage laboratory and supplier partnerships, including 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, and resolving discrepancies with scientists and data engineers.
• Build scalable operating systems using trackers, dashboards, SOPs, alerts, and AI agents to automate coordination, surface risks, and reduce manual follow-up.
• Keep pharmaceutical customers, AI research partners, laboratories, and internal teams aligned through communication, escalation, and reliable delivery.
• Manage SOWs, purchase orders, invoices, and project budgets; track spending against progress and identify opportunities to improve cost and turnaround.
• Measure and improve throughput, delivery reliability, and data quality across drug discovery, Translate, and AI training workflows.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager
• Education Level: No Education Listed