Leads the full lifecycle of clinical NGS diagnostic algorithms for oncology and liquid biopsy applications. Responsibilities include algorithm design, analytical validation, design control, regulatory readiness, variant calling, QC metric development, probabilistic modeling, machine learning, and validation pipeline automation. The role serves as technical authority for algorithm changes, supports regulatory submissions, and develops solutions for low-input, fragmented, and ultra-low-frequency genomic variants.
Are you motivated to participate in a dynamic, multi-tasking environment? Do you want to join a company that invests in its employees? Are you seeking a position where you can use your skills while continuing to be challenged and learn? Then we encourage you to dive deeper into this opportunity.
We believe in career development and empowering our employees. Not only do we provide career coaches internally, but we offer many training opportunities to expand your knowledge base! We have highly competitive benefits with a variety HMO and PPO options. We have company 401k match along with an Employee Stock Purchase Program. We have tuition reimbursement, leadership development, and even start employees off with 16 days of paid time off plus holidays. We offer wellness courses and have highly engaged employee resource groups. Come join the Neo team and be part of our amazing World Class Culture!
NeoGenomics is looking for a Principal Scientist Algorithm Lead – Clinical NGS Diagnostics who wants to learn to continue to learn in order to allow our company to grow. This is a remote position.
Now that you know what we're looking for in talent, let us tell you why you'd want to work at NeoGenomics:
As an employer, we promise to provide you with a purpose driven mission in which you have the opportunity to save lives by improving patient care through the exceptional work you perform. Together, we will become the world's leading cancer reference laboratory.
Position Summary:
As the Principal Scientist Algorithm Lead you will provide end‑to‑end scientific and technical leadership for clinical‑grade NGS diagnostic algorithms, with a primary focus on oncology and liquid biopsy applications. This role owns algorithm design, analytical validation, design control, and regulatory readiness, with an emphasis on improving sensitivity, robustness, and reproducibility across complex variant classes.
Responsibilities:
- Own the full lifecycle of clinical NGS algorithms under design control, including requirements definition, risk analysis, traceability to analytical claims, and design change impact assessment.
- Architect and lead automated analytical validation frameworks spanning accuracy, precision, sensitivity/LOD, specificity, linearity, and robustness for SNVs, indels, CNVs, structural variants, gene fusions, and RNA‑based assays.
- Define algorithm‑level error models, performance budgets, and acceptance criteria, driving systematic improvements in low‑VAF detection, background suppression, and assay‑specific artifact mitigation.
- Establish statistically rigorous approaches for truth set construction, reference materials, in silico mixing, and synthetic data generation to support scalable and reproducible validation.
- Serve as final technical authority on algorithm changes, including re‑validation scope, documentation strategy, and regulatory impact.
- Lead development and optimization of variant calling and signal extraction algorithms for DNA‑ and RNA‑based assays, including ultra‑deep sequencing and challenging genomic regions.
- Develop and track NGS‑based quality control metrics at the read, molecule, sample, and assay levels (e.g., coverage, uniformity, duplication/UMI yield, error rates, contamination, noise profiles) to monitor analytical performance and stability.
- Apply probabilistic modeling, Bayesian inference, and machine learning to improve sensitivity and specificity while maintaining interpretability and regulatory defensibility.
- Lead algorithm development for solid tumor and hematologic malignancy profiling, including tissue and liquid biopsy use cases.
- Address challenges specific to low‑input DNA/RNA, fragmented cfDNA, and ultra‑low‑allele‑frequency variants.
- Translate algorithm behavior and QC performance into clear, testable analytical claims aligned with CLIA, CAP, FDA, NYDoH, CLSI, and MolDx expectations.
- Author and review algorithm components of validation reports, design history documentation, and regulatory submissions.
Education, Experience & Qualifications:
- PhD in Bioinformatics, Computational Biology, Computer Science, Statistics, or a related quantitative field.
- 8+ years of experience developing algorithms for clinical NGS diagnostics, ideally in oncology.
- Deep expertise in SNV/indel, CNV, SV, fusion, and RNA analysis, NGS QC metrics, statistical modeling, and analytical performance evaluation.
- Demonstrated leadership in analytical validation and regulatory submissions (CLIA, CAP, FDA, NYDoH, MolDx).
- Hands‑on experience applying AI/ML methods to NGS data or biomarker development.
- Expert programming skills in Python and R; strong understanding of workflow orchestration and validation automation.
- Strong publication or presentation record in computational genomics or NGS diagnostics.
- Experience building QC‑driven, highly automated validation pipelines with rigorous statistical controls.
- Familiarity with payer evidence and reimbursement considerations for molecular diagnostics.
Similar Jobs
.png)
Artificial Intelligence • Cloud • Payments • Software • Business Intelligence • Generative AI • Automation
Lead product vision, strategy, adoption, roadmap prioritization, user research, metrics, and cross-functional execution for an AI-powered B2B insurance submissions platform. Partner across design, engineering, marketing, customer experience, and operations; manage integrations with adjacent products; resolve dependencies; communicate strategy and outcomes to senior leadership; and mentor other product managers.
Top Skills:
AgileAIApplied EpicConfluenceJIRA
Cloud • Software
Own strategic enterprise accounts across New England for ThousandEyes, driving new-logo acquisition and customer expansion. Build executive relationships, independently generate pipeline, leverage Cisco’s sales ecosystem, and lead complex enterprise sales cycles through technical evaluation, negotiation, and close. Manage six- and seven-figure transactions, develop strategic account plans, expand customers into $1M+ ARR relationships, and maintain quota attainment, pipeline coverage, and forecast accuracy.
Top Skills:
Cisco ThousandeyesCloud NetworkingCybersecurityEnterprise Technology SolutionsObservabilitySaaS
Artificial Intelligence • Professional Services • Business Intelligence • Consulting • Cybersecurity • Generative AI
Lead end-to-end NetSuite implementations as a functional consultant and team manager. Manage finance transformation initiatives, NetSuite order-to-cash, purchase-to-pay, and account-to-report workstreams, Advanced Revenue Management and SuiteBilling implementations, customizations, integrations, and testing. Lead onshore and offshore teams, address client needs, communicate complex concepts, and apply accounting and finance expertise to deliver effective technology solutions.
Top Skills:
Erp IntegrationsNetSuiteNetsuite Advanced Revenue ManagementNetsuite Multibook AccountingOracleSuitebilling
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
