Global Enrollment Systems Lead (AI-Enabled Oncology Trials)

Massive Bio, Inc.

23h

About The Position

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. We are hiring a Global Enrollment Systems Lead to design and optimize the operational engine that converts AI-matched patients into randomized trial participants at scale. This is not a coordination role. This is a systems architecture and throughput optimization role. You will: Own enrollment velocity end to end Map the full funnel from qualification → site referral → screening → consent → randomization Identify bottlenecks and drop-offs Reduce cycle time Increase throughput without proportional headcount growth Build scalable playbooks across countries You will work across internal teams (AI, clinical operations, customer success) and external stakeholders (sites, sponsors, CROs, networks) to eliminate friction and maximize conversion. This is a high-autonomy role with direct exposure to leadership and co-founders. As volume scales, you will build and lead a team to expand operational capacity. Think like an industrial engineer inside one of the most complex operational systems in healthcare. You will: Map and continuously refine the enrollment value stream Build dashboards tracking funnel performance at each stage Analyze conversion drop-offs and variance by country, site, and trial Model capacity constraints and identify system bottlenecks Reduce match-to-randomization cycle time Standardize scalable enrollment playbooks across regions Align AI outputs with real-world operational execution Improve screen failure rates through structured pre-qualification systems Increase enrollment throughput per FTE Create operational leverage as we grow This is a live, multi-country, multi-stakeholder system — not a theoretical exercise. You will be accountable for measurable impact: % reduction in match-to-randomization cycle time Improvement in qualification-to-screening conversion Reduction in screen failures Increase in enrollment throughput per trial Capacity scaling without linear headcount growth Country-level velocity optimization Funnel transparency through performance dashboards Enrollment speed is the product. You own it. This role is ideal for someone who: Thinks in systems, bottlenecks, and throughput Has led end-to-end operational pipelines in high-growth environments Loves reducing friction and optimizing complexity Builds dashboards and makes decisions based on data Is comfortable operating with ambiguity and building new functions Thrives in startup environments without bureaucracy Wants ownership, not supervision You might come from: Industrial engineering Operations in logistics or supply chain High-growth tech startups Healthcare services Consulting (operations focus) Private equity portfolio operations Clinical trials operations with a strong systems mindset

Requirements

5–8 years leading operational delivery in complex, multi-stakeholder environments
Demonstrated ownership of a conversion funnel or delivery pipeline end to end
Experience improving throughput and reducing cycle time systematically
Track record of scaling an operational function without linear headcount growth
Strong analytical capability (Excel, dashboards, data modeling, PowerPoint)
Structured project management discipline across multiple parallel workstreams
High energy and resilience in fast-moving startup environments

Nice To Haves

Healthcare, life sciences, or clinical trials experience
Oncology knowledge (biomarker testing, treatment sequencing)
Experience working with AI-enabled platforms
Familiarity with patient recruitment vendors or CRO operations
PMP or similar structured project management training

Responsibilities

Own enrollment velocity end to end
Map the full funnel from qualification → site referral → screening → consent → randomization
Identify bottlenecks and drop-offs
Reduce cycle time
Increase throughput without proportional headcount growth
Build scalable playbooks across countries
Map and continuously refine the enrollment value stream
Build dashboards tracking funnel performance at each stage
Analyze conversion drop-offs and variance by country, site, and trial
Model capacity constraints and identify system bottlenecks
Reduce match-to-randomization cycle time
Standardize scalable enrollment playbooks across regions
Align AI outputs with real-world operational execution
Improve screen failure rates through structured pre-qualification systems
Increase enrollment throughput per FTE
Create operational leverage as we grow