Director of Clinical Data Management

The Director of Clinical Data Management will establish and lead the clinical data management function at Pathos. You will own clinical data collection, cleaning, and integrity across our oncology trials, ensuring our datasets are ready for analysis, regulatory submissions, and the next development decision. You will report to the Vice President, Head of Clinical Operations.

This is the first CDM hire at Pathos. There is no existing playbook. You will write it. You will define how Pathos collects, cleans, and locks clinical data in a company built on small teams and AI agents, and you will set the standard for what audit ready trial data looks like in this operating model.

The role sits at the intersection of clinical data discipline and an AI native operating model. You will spend less time chasing CRO status reports and more time on the data questions that move trials forward, because AI agents will absorb the routine query resolution, status tracking, discrepancy review, and document compilation work that traditionally consumed a CDM Director’s calendar.

What You Will Do

Own clinical data strategy and oversight

• Lead oversight of data management for outsourced clinical trials, including project planning, vendor coordination, internal review cycles, data cleaning, and approval of deliverables.
• Oversee CRO and vendor activities to ensure GCP compliance and execution against protocols and SOPs.
• Own consistency across trials and programs: CRF design and standards, Data Management Plans, CRF annotation and completion guidelines, edit check specifications, data entry and query status tracking, and database lock.
• Drive timely database lock, data quality, and readiness for statistical analysis and regulatory submissions.
• Direct AI agents to draft DMPs, edit check specs, and reconciliation reports, and apply your judgment to the final product.

Execute vendor and CRO management

• Manage CROs and vendors delivering CDM services, holding them to timelines, budgets, and quality standards.
• Develop and monitor Data Management Plans, Data Review Plans, and data transfer specifications.
• Resolve complex data issues, queries, and discrepancies in partnership with clinical and statistical teams.
• Use AI agents to compare vendor deliverables against specifications, surface drift early, and prepare structured feedback for vendor reviews.

Build cross functional partnerships

• Serve as the primary CDM partner on every study team.
• Partner with Biostatistics, Clinical Operations, Medical Monitoring, and Data Science colleagues so that data supports trial endpoints and regulatory deliverables.
• Collaborate on the integration of clinical trial data with Pathos AI platforms and real world data sources so that operational data feeds back into model performance and decision support.

Lead, scale, and stay compliant

• Build and scale the CDM function as the company grows, including hiring and mentoring future staff.
• Develop SOPs, best practices, and quality frameworks that meet GCP, ICH, CDISC, and 21 CFR Part 11 expectations.
• Contribute to portfolio level planning and operational strategy, and translate CDM signals into actionable input for Clinical Operations leadership.

Do you have experience in Vendor relationship management?, Do you have a Master’s degree?, * Bachelor’s or Master’s degree in Life Sciences, Data Management, or a related field.

• 10 or more years of progressive experience in clinical data management, including leadership of oncology trials.
• Deep working knowledge of EDC systems such as Medidata Rave, Veeva CDMS, or Oracle InForm, and clinical data standards including CDISC, SDTM, and ADaM.
• Demonstrated ability to manage CROs and vendors against quality, timeline, and budget commitments.
• Strong command of GCP, ICH, FDA, CDISC, GCDMP, 21 CFR Part 11, MedDRA, and WHO Drug Dictionaries, and how they apply in daily CDM practice.

Strongly Preferred

• Experience operating in a flat, builder oriented organization where you specify, orchestrate, and ship rather than manage process.

• Experience gathering requirements and writing specifications for database integrations, including ePRO, central and local laboratory data uploads, supply management, IVRS, and IWRS.
• Experience building a CDM function from the ground up or substantially rebuilding one in a small company environment.
• Comfort orchestrating AI tools or agentic workflows in clinical data work, and clear instinct for where automation belongs and where human review must stay.

Pathos is building a next-generation biotech with AI at the core. Not as a feature, but as the operating system for how medicines get developed. We believe most drugs don’t fail because the science was wrong. They fail because they were tested in the wrong patients, with the wrong assumptions, in trials that couldn’t answer the real question: who benefits, and why?

Pathos exists to change that. We’re building the largest foundation model in oncology and pairing it with proprietary AI systems, deep oncology expertise, and 200+ petabytes of multimodal data linked to patient outcomes, so we can make development decisions with more precision, much earlier.

This is not theoretical. We’re well-capitalized and have the leadership to build a generational company. We invest in and advance our own clinical-stage programs, using our AI platform to sharpen trial design, patient selection and biomarker strategy. So therapies reach the patients most likely to benefit, sooner.

How We Build

Pathos does not operate like a traditional biotech. There is no middle management. There are no layers of approval. The company is designed, from the ground up, around small teams of 2-4 subject matter experts who each command hundreds of AI agents to do the work that used to require dozens of people.

Everyone builds. Everyone ships. Every function at Pathos - from clinical execution to asset selection to the foundation model itself - runs on this model. Our product velocity delivers meaningful outcomes in hours instead of weeks. This is not a future aspiration. It is how we operate today.

The people who thrive here are operators: deep experts who can specify what needs to happen, orchestrate AI agents to execute at scale, and make high-judgment calls that compound over time. If you have spent your career building and shipping AI systems at scale, this is the environment where that experience becomes a superpower., Pathos does not operate like a traditional biotech. There is no middle management. There are no layers of approval. The company is designed, from the ground up, around small teams of 2-4 subject-matter experts who each command hundreds of AI agents to do the work that used to require dozens of people.

Everyone builds. Everyone ships. Every function at Pathos - from clinical execution to asset selection to the foundation model itself - runs on this model. Our product velocity delivers meaningful outcomes in hours instead of weeks. This is not a future aspiration. It is how we operate today.

The people who thrive here are operators: deep experts who can specify what needs to happen, orchestrate AI agents to execute at scale, and make high-judgment calls that compound over time. If you have spent your career building and shipping AI systems at scale, this is the environment where that experience becomes a superpower.