Clinical Operations Analyst

Massive Bio; Perímetro Urbano Medellín; Remote; COP 191,528,000 - 287,292,000; Full time

Job summary

Massive Bio, Inc. is seeking a Clinical Operations Analyst to support daily operations of our Clinical Operations team.

You will review patient records, assess trial eligibility, and help matched patients progress from referral to enrollment while tracking bottlenecks and implementing process improvements. You will collaborate with Clinical Operations, Product, and Engineering teams, with opportunities to contribute across screening, enrollment, and SOP development.

Qualifications

• MD or equivalent medical degree.
• 3+ years of experience in clinical operations, clinical research, or clinical practice.
• Working knowledge of the clinical trial process, including inclusion and exclusion criteria, screening, informed consent, and enrollment.
• Strong analytical skills; comfortable working with data in Excel, dashboards, or reporting tools.
• Team management experience, in any setting, is a strong plus.
• Professional working proficiency in English, written and spoken.
• Clear written communication, with the ability to document findings and explain them to clinical and non-clinical stakeholders.
• Comfort working in a fast-moving, remote, cross-functional environment.

Responsibilities

• Track and report on the referral-to-enrollment funnel across active trials, from eligibility review and site referral through screening, consent, and enrollment.
• Analyze where cases slow down or drop off, identify the causes, and turn findings into practical process improvements.
• Monitor the quality and turnaround of clinical review work, including eligibility assessments and AI-abstracted clinical data, and flag issues early.
• Build and maintain the trackers, dashboards, and reports the team and leadership use to manage daily operations.
• Apply oncology clinical knowledge to support eligibility review on complex cases.
• Write and maintain SOPs, workflows, and training materials, and help onboard and train new team members.
• Work with Product and Engineering to turn recurring operational issues into improvements in our AI-driven patient-to-trial matching workflows.
• Partner with patient engagement, enrollment, and other internal teams to remove blockers and keep cases moving.

Skills

Analytical skills

English proficiency

Team management

Communication skills

Remote work adaptability

Oncology exposure

Education

MD or equivalent medical degree

Tools

Excel

Dashboards

Job description

About Massive Bio

Every cancer patient deserves access to treatment options. Massive Bio is an AI-powered precision medicine platform transforming how cancer patients discover and access clinical trials by eliminating the barriers of geography, financial constraints, and information asymmetry that have historically limited enrollment.

Founded in 2015 and headquartered in the US, Massive Bio is scaling its impact globally by powering operations across multiple countries and bringing innovative cancer treatment options to a rapidly growing and diverse population of patients. Through our proprietary AI platform, we connect individuals to clinical trials worldwide and partner with leading pharmaceutical companies, contract research organizations (CROs), and healthcare systems to accelerate drug development and expand equitable access to cutting-edge therapies.

About the Role

The Clinical Operations Analyst supports the daily work of our Clinical Operations team, where physicians use our AI-powered platform to review patient records, assess clinical trial eligibility, and support matched patients from referral to enrollment. In this role, you will track how that work is running, find where cases slow down or drop off, and help the team fix it.

You will work closely with Clinical Operations, Product, and Engineering teams, and with the internal teams that support patients through screening and enrollment. We are open to a broad range of experience levels.

What You’ll Do

• Track and report on the referral-to-enrollment funnel across active trials, from eligibility review and site referral through screening, consent, and enrollment.

• Analyze where cases slow down or drop off, identify the causes, and turn findings into practical process improvements.

• Monitor the quality and turnaround of clinical review work, including eligibility assessments and AI-abstracted clinical data, and flag issues early.

• Build and maintain the trackers, dashboards, and reports the team and leadership use to manage daily operations.

• Apply oncology clinical knowledge to support eligibility review on complex cases.

• Write and maintain SOPs, workflows, and training materials, and help onboard and train new team members.

• Work with Product and Engineering to turn recurring operational issues into improvements in our AI-driven patient-to-trial matching workflows.

• Partner with patient engagement, enrollment, and other internal teams to remove blockers and keep cases moving.

What We’re Looking For

• MD or equivalent medical degree.

• 3+ years of experience in clinical operations, clinical research, or clinical practice; oncology or hematology exposure is a strong plus.

• Working knowledge of the clinical trial process, including inclusion and exclusion criteria, screening, informed consent, and enrollment.

• Strong analytical skills; comfortable working with data in Excel, dashboards, or reporting tools.

• Team management experience, in any setting, is a strong plus.

• Professional working proficiency in English, written and spoken.

• Clear written communication, with the ability to document findings and explain them to clinical and non-clinical stakeholders.

• Comfort working in a fast-moving, remote, cross-functional environment.

Nice to Have

• Experience at a CRO, research site, site network, or pharmaceutical sponsor.

• Experience with CTMS, EDC, or CRM systems.

• Experience with patient recruitment or enrollment programs.

• Experience building processes, SOPs, or training programs from scratch.

• Interest in AI and machine learning applications in healthcare.