---
title: 'Data Operations Manager, Scientific Data at Axiom'
canonical: 'https://feeny.ai/job/data-operations-manager-scientific-data-axiom-south-san-francisco-f2svqkhwfb64'
type: 'job'
last_seen: '2026-11-01'
---

# Data Operations Manager, Scientific Data at Axiom

- **Company:** Axiom
- **Location:** South San Francisco, CA
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-11-01
- **Last confirmed live:** 2026-11-01
- **Apply:** https://jobs.ashbyhq.com/axiombio/f0828136-6ff2-4297-bb9a-69cc54d61148

## Job description

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.

## About Axiom

## Company Overview
- **One-liner**: Axiom builds an AI platform that predicts human drug toxicity from lab data, helping pharmaceutical companies develop safer medicines with less animal testing.
- **Entity Type**: Private (Seed round, April 2025)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2024
- **Founders**: Brandon White, Alex Beatson

## Core Business
- **Primary industry**: Biotechnology Research / Artificial Intelligence for Drug Discovery
- **Target customers**: B2B – pharmaceutical and biotech companies, drug discovery teams
- **Mission or purpose statement**: "Understand drug toxicity before it reaches humans" – using “frontier intelligence” to end unexpected drug toxicity and reduce clinical trial failures.

## Products & Services
- **Toxicity Prediction Platform**: An agentic AI system that connects experimental data (cell painting, mass spectrometry, metabolism assays) to clinical outcomes. Provides mechanistic, exposure-aware risk assessments early in discovery. (SaaS/API platform)

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Key Metric**: Seed round (April 2025) with participation from at least three investors; total funding amount not disclosed.
- **Notable Investors/Partners**: Amplify Partners, Abstract VC, Dimension Capital, Zetta Venture Partners, CRV; advisors include Jeffrey Dean (Google DeepMind), Yvonne Will (former Pfizer), Nicholas Meanwell (medicinal chemistry leader).
- **Growth Signals**: Headcount grew 108% YoY (22 employees); LinkedIn followers grew 287% YoY; website traffic up 277% YoY; actively hiring for ML, data, and platform engineering roles.

## Competitive Advantages
- **Human-relevant data core**: Models trained on primary human hepatocytes and clinical outcomes rather than animal models, directly addressing the 90% clinical failure rate.
- **Mechanistic AI**: Provides interpretable, exposure-aware risk profiles instead of black-box hazard flags, enabling chemists to modify compounds.
- **World-class advisory board**: Deep expertise from pharma safety, medicinal chemistry, and ML (e.g., Nicholas Meanwell, Yvonne Will, Jeffrey Dean).

## Strategic Focus
- Replace traditional animal-based toxicity tests with AI-driven, human-relevant predictions.
- Expand from liver toxicity (DILI) to other organ systems and broader safety readouts.
- Scale customer integrations via enterprise SaaS and collaborative research partnerships.

## Why Work Here
- **Culture**: Fast-growing startup (founded 2024) with a tight-knit team of ~22, emphasizing both scientific rigor and engineering excellence.
- **Work environment**: Hybrid/remote-friendly (roles listed as “In-Office or Remote”); offices in San Francisco with remote team members in Canada and Israel.
- **Engineering culture**: Strong ML and platform engineering focus; stack includes Python, PyTorch, React, Typescript, and scientific libraries.
- **Open roles** (as of mid-2026): Platform Engineer, Data Engineer, ML Researcher, Product Engineer, Computational Scientist (Mass Spectrometry) – posted on [jobs.ashbyhq.com](https://jobs.ashbyhq.com/axiombio) and [Built In](https://builtin.com/company/axiom-bio/jobs).

## Sources
1. [axi.om/company](https://www.axi.om/company)
2. [linkedin.com/company/axiombio](https://www.linkedin.com/company/axiombio)
3. [axi.om/mission](https://www.axi.om/mission)
4. [builtin.com/company/axiom-bio/jobs](https://builtin.com/company/axiom-bio/jobs)

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