Associate Director, Oncology Algorithm & Data Products

POSITION SUMMARY:

We are seeking an Associate Director or Director of Product Management to spearhead the strategy, development, and commercialization of our oncology diagnostic algorithms and data products. Powered by our proprietary cell-free DNA (cfDNA) platform and one of the world's largest longitudinal clinico-genomic datasets, this role translates complex machine learning outputs into validated standard-of-care tools for cancer detection and biopharma partnerships. Reporting directly to the Senior Director of Product Management - Oncology Innovations, this position operates with broad technical and commercial autonomy to bring algorithm-driven solutions from concept through analytical validation. This is an ownership role for a builder who wants to eliminate functional silos and use data to pressure-test product assumptions in a fast-paced, science-driven environment.

PRIMARY RESPONSIBILITIES:

Product Strategy and Roadmap Ownership

• Own the multi-year product roadmap for AI-powered diagnostics, resolving complex data science and commercial priorities by grounding product milestones in clinical validation data
• Isolate and pressure-test high-value innovation opportunities to build a differentiated pipeline of AI-enabled diagnostic algorithms and biopharma data products
• Translate large, longitudinal genomic and real-world datasets into clinically meaningful, regulatory-ready algorithms that address unmet clinical needs
• Establish clear, unvarnished product requirements and data validation metrics for prospective algorithm pipelines

Algorithm Development and Lifecycle Management

• Lead cross-functional execution across the full lifecycle—from initial concept and analytical validation through health-authority navigation and commercial launch
• Partner closely with Bioinformatics, AI Research, and Data Science teams to translate next-generation sequencing data into robust algorithms supporting molecular residual disease (MRD) monitoring and therapy response prediction
• Advance priority algorithm concepts through proof-of-concept testing and coordinate analytical validation strategies
• Formulate and launch data product pilots with target biopharma and clinical trial partners to maximize data utility and commercial relevance

Cross-Functional Leadership and Stakeholder Alignment

• Align matrixed scientific, clinical, regulatory, and commercial teams to keep complex, data-driven products moving forward past operational bottlenecks
• Coordinate product execution loops with teams across Clinical Genomics Database (CGDB), AI Research, and Biopharma Business Development
• Communicate with technical and scientific precision when engaging biopharma partners and academic key opinion leaders (KOLs)
• Maintain a transparent, fast-iterating product methodology, utilizing data to guide decisions and ensuring algorithms are commercially viable and scalable

QUALIFICATIONS:

• Advanced degree (PhD, MD, MS, or MBA preferred) paired with 8+ years of total experience within biotechnology, diagnostics, or pharma-facing data products.
• 5+ years of dedicated product management experience within molecular diagnostics, genomics, or life sciences data platforms
• Documented track record of leading complex data or diagnostic products completely through the lifecycle from early concept to on-market commercialization
• Direct experience partnering with bioinformatics, computational biology, or data science teams to develop or commercialize algorithm-driven software assets
• Deep experience working with large-scale genomic datasets, multi-omic frameworks, or clinical real-world evidence (RWD)

KNOWLEDGE, SKILLS, AND ABILITIES:

• Deep structural understanding of oncology diagnostics, biomarker validation workflows, clinical trial architectures, and emerging liquid biopsy technology
• Technical data fluency with the capability to engage as a peer with artificial intelligence researchers and computational biologists
• Ability to navigate evolving health-authority regulatory frameworks governing machine learning and AI-enabled diagnostics
• Strong ownership mindset with a proven record of balancing multiple structural innovation opportunities under tight timelines
• Precise written and verbal communication styles with a commitment to scientific rigor and data transparency