Jobs at Freenome

Develop, optimize, and characterize NGS-based assays and automated workflows including extraction, library prep, target capture, and sequencing. Operate and maintain NGS instruments and automated liquid handlers, perform reagent QC, troubleshoot and improve processes, and transfer methods to Operations. Record results in electronic lab notebooks, author protocols and work instructions, and collaborate with scientists, automation engineers, Quality, and Regulatory to support scaled clinical lab implementation under cGLP.

Lead and scale enterprise-wide revenue cycle operations, overseeing patient intake, billing, collections, payer contracting, compliance, KPIs, budgeting, and team development. Design and implement AI/automation-enabled revenue cycle infrastructure, collaborate cross-functionally with Sales, Market Access, and Commercial Operations, and present strategic recommendations to executive leadership to optimize reimbursement and reduce denials.

Design, build, and deploy scalable distributed deep learning pipelines and infrastructure. Optimize hardware utilization, profile and benchmark training, manage large datasets, and enable reproducible ML workflows in cloud environments. Collaborate with ML scientists and engineers to align pipelines with research goals and drive performance, reliability, and operational best practices for large-scale model development.

Lead computational research for early cancer detection using cfDNA. Design and execute NGS assay and bioinformatics pipeline development, analyze molecular and clinical data, iterate assays with wet lab partners, and drive hypothesis-driven projects from ideation through implementation.

Design and execute research for early, noninvasive cancer detection using cfDNA. Lead molecular and clinical data analysis, develop high-throughput NGS bioinformatics pipelines, collaborate with wet lab teams to assess assay performance and iterate on experimental methods, and propose computational improvements for assays and models.

Sell and drive adoption of Freenome's early cancer detection tests and digital health platform across health systems. Build executive relationships, negotiate and close institutional contracts, partner on implementation (EMR/UX), capture CRM data, and provide customer feedback to product and marketing to grow programmatic screening adoption.

Lead biostatistician supporting study design, statistical analysis, and reporting for IVD clinical studies. Provide technical oversight, prepare protocol statistical sections, review TFLs, manage programmers, interact with regulators, and support publications, presentations, SOPs, and cross-functional stakeholders to enable regulatory submissions and clinical development.

The Senior Research Associate will develop clinical-grade assays using NGS technologies, design experiments, analyze data, and collaborate cross-functionally to optimize performance and support cancer diagnostics.

The Strategic Account Executive will drive adoption of Freenome's cancer detection solutions by networking with health systems, negotiating contracts, and collaborating with teams to implement tools that promote sales growth.

The Strategic Account Executive will drive programmatic adoption of cancer detection tests in health systems, manage relationships, negotiate contracts, and analyze market opportunities.

Lead FP&A for a scaling diagnostics company: partner with R&D, Commercial, and Ops; drive budgeting, forecasting, KPI reporting, financial modeling, system improvements, and AI-enabled automation to inform strategic decisions and maintain public-company controls.

The Strategic Account Executive will drive the adoption of Freenome's early cancer detection solutions within health systems, meeting sales goals and building strong client relationships. Responsibilities include negotiating contracts, collaborating with stakeholders, providing market feedback, and developing strategic plans for growth.

Lead end-to-end platform engineering projects to build and operate a multi-tenant data lakehouse and scalable compute infrastructure, partner with cross-functional teams, improve reliability/observability, support platform users, and drive platform usability and ML/analytics enablement.

Lead the execution of Freenome's engineering initiatives by managing software development for the Commercial Data Platform. Collaborate with stakeholders to define requirements and create a technical roadmap, ensuring compliance with regulatory standards.

Design, implement, and maintain on‑prem and cloud network infrastructure for HQ and global standards. Lead Zero Trust, firewall and VPN deployments, collaborate with engineering and lab teams, produce documentation, and troubleshoot network incidents to ensure availability and security.

Lead strategy, architecture, and operations for a regulatory-grade Real World Data (RWD) platform. Oversee ingestion, harmonization, curation, and governance of EHR, claims, imaging, and molecular data; implement AI/NLP workflows; support regulatory submissions, RWE generation, clinical analyses, and commercialization. Build and manage a high-performing informatics team, cross-functional partnerships, and scalable data pipelines.

Lead Freenome's product portfolio across assay development, digital health, and data platform. Define product strategy, prioritize R&D and launches, integrate AI/agentic workflows, manage and grow product teams, align cross-functional stakeholders, track KPIs, and drive customer and market-informed product decisions to advance early cancer detection and patient access.

Develop and validate NGS-based DNA assays, run and characterize automated assays, collect and analyze high-quality experimental data, collaborate with computational and engineering teams, present results, troubleshoot experiments, and improve lab processes in a regulated, high-throughput environment.

Perform NGS-based assay development and validation for DNA-based, blood analytes. Execute and characterize automated assays, gather and analyze experimental data, troubleshoot with guidance, present results cross-functionally, and support process improvements in a regulated, high-throughput lab.

Lead development and evaluation of computational models to identify cancer molecular signatures from high-throughput assays. Design statistical models, perform rigorous analyses on genomics, epigenomics, transcriptomics, and proteomics data, drive research projects, collaborate with ML scientists and wet-lab teams, and mentor computational biologists to translate research into clinical diagnostics.