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
Software • Analytics • Hospitality
Leads revenue recognition, billing, accounts receivable, collections, audit readiness, and financial control operations. Ensures ASC 606 and GAAP compliance, manages billing platforms and ERP integrations, drives automation and AI adoption, develops scalable processes, partners cross-functionally, reports financial metrics, and supervises accounting staff. Requires extensive revenue accounting and billing experience in SaaS or software, management expertise, and strong technical accounting knowledge.
Top Skills:
Ai-Enabled Accounting Automation ToolsBilling PlatformsErp SystemsExcelMicrosoft OutlookMicrosoft WordNetSuiteOracleSAP
Software • Analytics • Hospitality
Leads revenue recognition, billing, accounts receivable, collections, audit readiness, and financial controls. Owns ASC 606 compliance, billing systems, process automation, AI-enabled accounting improvements, reporting, and cross-functional alignment. Manages and mentors the accounting team while supporting scalable revenue operations and public-company readiness.
Top Skills:
Ai-Enabled Automation ToolsAsc 606GaapExcelMicrosoft OutlookMicrosoft WordNetSuiteOracleSAP
Software • Analytics • Hospitality
Leads revenue recognition, billing, accounts receivable, collections, audit readiness, and ASC 606 compliance. Oversees billing systems and ERP integrations, develops scalable financial controls and processes, and drives automation and AI adoption. Partners cross-functionally with Sales Ops, Legal, Product, FP&A, and IT. Manages and mentors the accounting team, delivers financial reporting to leadership, and supports public-company readiness and internal and external audits.
Top Skills:
Asc 606Erp SystemsGaapExcelMicrosoft OutlookMicrosoft WordNetSuiteOracleSAP
What you need to know about the Chicago Tech Scene
With vibrant neighborhoods, great food and more affordable housing than either coast, Chicago might be the most liveable major tech hub. It is the birthplace of modern commodities and futures trading, a national hub for logistics and commerce, and home to the American Medical Association and the American Bar Association. This diverse blend of industry influences has helped Chicago emerge as a major player in verticals like fintech, biotechnology, legal tech, e-commerce and logistics technology. It’s also a major hiring center for tech companies on both coasts.
Key Facts About Chicago Tech
- Number of Tech Workers: 245,800; 5.2% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: McDonald’s, John Deere, Boeing, Morningstar
- Key Industries: Artificial intelligence, biotechnology, fintech, software, logistics technology
- Funding Landscape: $2.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Pritzker Group Venture Capital, Arch Venture Partners, MATH Venture Partners, Jump Capital, Hyde Park Venture Partners
- Research Centers and Universities: Northwestern University, University of Chicago, University of Illinois Urbana-Champaign, Illinois Institute of Technology, Argonne National Laboratory, Fermi National Accelerator Laboratory
