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RDI - Your IVD CRO in Los Angeles is seeking a Clinical Data Manager to ensure data integrity across multiple studies. This role requires ownership of subject-level data and deep investigative skills to trace discrepancies.
The ideal candidate has over 3 years of experience in clinical data management, particularly in regulated environments. Responsibilities include ensuring data accuracy and being accountable for datasets that go to the FDA.
Additionally, you'll help shape new data systems to improve data accuracy and reliability.
Own the data. Find the true story it's hiding.
At RDI Trials, we're building a different kind of CRO.
We are an IVD-focused contract research organization. Since 2008 we've run 300+ diagnostic trials for the largest test makers in the world. Our clinical operations team is sharp, motivated, and runs its own workload well — what they need now is someone to raise the ceiling on monitoring craft.
This is not a traditional, process-heavy environment.
We are a small team that moves fast and expects people to take real ownership. There's no passing things along or waiting for direction. If something needs to get done, you step in and figure it out.
The pace is high. The expectations are high. But for the right person, it's a place where you can learn quickly and have real impact.
This is a place for people who want to build, not just maintain.
We punch above our weight class — a 30-person company running the workload of a CRO twice our size. That happens because of how we work, not how big we are.
We move with speed and discipline. We own outcomes, not tasks. Precision is non-negotiable in our work, so it's non-negotiable internally. Grit matters here — but we'd rather build the systems that scale.
The CEO sets the pace. The COO runs the operation. Leadership is accessible — you'll be in the room. Feedback is fast and unvarnished, and the worst thing you can do is hide a problem.
We just signed the largest contract in company history. The next 18 months will stretch every function, including this one.
When a new assay disagrees with the predicate, somebody has to figure out why. Is it the test? The specimen? The site? A single keystroke at data entry? Most "data people" report the discordance and move on. We're looking for the one who treats it as a case to crack.
You’ll own subject- and sample-level data across 20-30 concurrent method‑comparison and specimen‑collection studies — and your real job is to make sure the dataset tells the truth. Not the convenient version. Not the version that makes a result look cleaner than it is. What actually happened. You check every cell because the truth lives in the cells, and you chase every anomaly to root cause because "looks off" is where the work starts.