Data Operations Manager, Scientific Data

Axiom • South San Francisco, CA

3d

About The Position

Own operational delivery of Axiom’s 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, from experimental planning through validated data delivery, while managing capacity, dependencies, timelines, and handoffs.

The role manages compound sourcing, purchasing, sample manifests, inventory, international shipping, and customs documentation. It also builds and manages laboratory and supplier partnerships, sets specifications and acceptance criteria, and protects data integrity by reconciling compound identities, barcodes, sample histories, experimental metadata, and incoming results with scientists and data engineers.

Build scalable operating systems—including trackers, dashboards, SOPs, alerts, and AI agents—to automate coordination, surface risks early, and reduce manual follow-up. Keep customers, AI research partners, laboratories, and internal teams aligned; manage SOWs, purchase orders, invoices, and project budgets; and improve throughput, delivery reliability, and data quality across Axiom’s drug discovery, Translate, 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, spreadsheets, SQL, Python, or other tools to investigate problems and make operational decisions.
• A track record of 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 aligning customers, researchers, and vendors 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 high-quality experimental data improves models and scientific agents.
• Habit of using AI tools and automation to improve work, with the judgment to verify outputs and maintain accountability.
• Data management and analysis skills using spreadsheets, SQL, Python, dashboards, and automated reconciliation and validation tools.
• Program planning skills, including dependency tracking, capacity planning, risk management, and quantitative process improvement.
• Workflow automation and AI agent skills for tracking deliverables, reconciling records, coordinating handoffs, and surfacing exceptions.
• Vendor and commercial operations skills, including SOWs, purchase orders, invoices, budgets, and performance tracking.
• Compound procurement, supplier coordination, inventory management, international shipping, and customs documentation skills.
• Scientific operations knowledge, including experiment scheduling, sample tracking, compound identity management, and laboratory data delivery.
• Ability to create clear SOPs, documentation, acceptance criteria, and escalation processes for internal teams and external partners.

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, establishing 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 clear communication, timely 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