Oncologist

$380/hr

rate as listed

Workload: ~15h/week
Engagement: Project-based
Location: Location not stated
Field: Medical

Evaluate and develop oncology cases that test AI reasoning about treatment decisions, clinical trial design and patient eligibility. This remote project is for actively practicing US medical oncologists or hematologist-oncologists with direct clinical trial experience.

The work

You will create realistic oncology scenarios designed to reveal weaknesses in AI-generated clinical reasoning, especially around trial eligibility, protocol design and treatment selection. Day-to-day contributions may include reviewing model outputs for missed diagnoses, flawed logic, incomplete rationales, unsafe recommendations and departures from current standards of care.

What Mercor screens for

Mercor verifies medical license status, fellowship completion and current clinical practice. Screening also focuses on direct involvement in oncology trials, command of protocol eligibility and RECIST criteria, familiarity with FDA-related requirements, and the ability to explain clinical judgments precisely in writing.

Logistics

The project is remote and short term, with possible extension based on performance. The listing does not state typical weekly hours or confirm whether all work can be completed asynchronously, and final placement requires confirmation by the project team before the start date.

The listing provides this observed pay band:

Pay band: $380/hr

What they look for

Active, unrestricted US medical license
MD or DO with completed fellowship in medical oncology or hematology/oncology
Current US clinical practice involving oncology patients
Direct experience with oncology clinical trials as a principal investigator, sub-investigator or treating physician
Clinical trial protocol, patient eligibility, FDA and RECIST expertise
Written evaluation of oncology reasoning, accuracy and patient safety

Included with this listing

Interview prep — 10 questions

Matched to what this platform's screening actually measures. Answer each out loud in 60–90 seconds: claim → concrete example → implication.

What it tests: This verifies fellowship completion, active patient care in the United States and the depth and recency of post-fellowship oncology experience.
A strong answer: Give the fellowship specialty and completion date, current practice setting, patient population, disease areas and approximate clinical workload. Clearly separate post-fellowship practice from training years.
Where people lose it: Candidates lose points by describing an oncology-adjacent academic or administrative role without confirming that they currently see oncology patients.

Summary, eligibility guidance and screening preparation are prepared by Sidequest from the platform's posting. Check the source listing before applying.

MEDICINE on Sidequest

What medicine AI work pays

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