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Senior Computational Biologist, Oncology

Pathos · New York City, NY, United States · On Site · Active · $170,000–$210,000 / year · Rippling ATS

Job facts

Field	Value
Company	Pathos
Title	Senior Computational Biologist, Oncology
Normalized title	-
Department / team	Computational Biology
Location	New York City, NY, United States
Work model	On Site
Employment type	Full Time
Salary	$170,000–$210,000 / year
Status	active
ATS provider	Rippling ATS
Posted / first seen	2026-01-09 / 2026-05-29
Changed / last seen	2026-06-06 / 2026-06-06

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Provider filtered search	The same provider as a filtered job collection.	Open
City jobs	Active postings in New York City.	Open
Department jobs	Active postings in Computational Biology.	Open
Work model jobs	Active On Site postings.	Open
Lifecycle events	Open, update, close, and reopen events for this posting.	Open
Original posting	Canonical source or apply URL captured from the ATS.	Open

Linked records

Company	Pathos
Source	2d66e9b5-1b63-475c-a03a-943980720722
ATS provider	Rippling ATS

Description

company Drug development shouldn’t be guesswork, not when patients are waiting. Pathos is building a next-generation biotech with AI at the core. Not as a feature, but as the operating system for how medicines get developed. We believe most drugs don’t fail because the science was wrong. They fail because they were tested in the wrong patients, with the wrong assumptions, in trials that couldn’t answer the real question: who benefits, and why? Pathos exists to change that. We’re building the largest foundation model in oncology and pairing it with proprietary AI systems, deep oncology expertise, and 200+ petabytes of multimodal data linked to patient outcomes, so we can make development decisions with more precision, much earlier. This is not theoretical. We’re well-capitalized and have the leadership to build a generational company. We invest in and advance our own clinical-stage programs, using our AI platform to sharpen trial design, patient selection and biomarker strategy. So therapies reach the patients most likely to benefit, sooner. How We Build Pathos does not operate like a traditional biotech. There is no middle management. There are no layers of approval. The company is designed, from the ground up, around small teams of 2–4 subject-matter experts who each command hundreds of AI agents to do the work that used to require dozens of people. Everyone builds. Everyone ships. Every function at Pathos — from clinical execution to asset selection to the foundation model itself — runs on this model. Our product velocity delivers meaningful outcomes in hours instead of weeks. This is not a future aspiration. It is how we operate today. The people who thrive here are operators: deep experts who can specify what needs to happen, orchestrate AI agents to execute at scale, and make high-judgment calls that compound over time. If you have spent your career building and shipping AI systems at scale, this is the environment where that experience becomes a superpower. role About the Role Pathos is building an AI-native biotech platform that turns real-world data and multimodal models into translational biomarker insights that directly shape drug development decisions—from early target validation through late-stage patient selection. We are redefining how oncology drug development is done: integrated, data-driven, and built from first principles. As a Senior Computational Biologist, you will sit at the intersection of genomics, translational science, and clinical development. You will own and evolve genomics and biomarker pipelines that support our internal and in-licensed oncology assets, with a particular focus on mechanism-based biomarkers, response predictors, resistance biology, and patient stratification. Your work will span discovery through Phase 1/2 clinical trials, with direct impact on indication selection, dose expansion strategy, and Go/No-Go decisions. You will generate and test biomarker hypotheses using deep genomic and multi-omic data derived from both external cohorts and Pathos-sponsored clinical trials, translating complex molecular signals into actionable insights for clinicians, program teams, and leadership. This role requires not just analytical excellence, but a strong understanding of how biomarkers are operationalized in real drug development settings. If you want to apply cutting-edge computational and genomics methods to problems that directly determine how cancer drugs are developed and deployed, this is the place to do the most meaningful work of your career. Key Responsibilities Design, build, and maintain end-to-end translational genomics pipelines supporting oncology drug programs, including RNA-seq, DNA (SNV/CNV/structural variants), and multi-omic integration. Generate and prioritize genomically grounded hypotheses tailored to different therapeutic modalities, including: Target dependency and pathway activation for small molecules Expression, heterogeneity, and spatial context for mAbs, bispecifics, and ADCs Biomarkers of payload sensitivity, internalization, and resistance for ADC programs Lead biomarker discovery and validation efforts across preclinical, translational, and clinical datasets, with a focus on: Predictive and pharmacodynamic biomarkers MOA and pathway activity signatures Resistance and escape mechanisms Analyze and interpret clinical trial biomarker data (Phase 1/2), linking molecular profiles to response, durability, safety, and survival endpoints. Partner closely with clinical, translational, and regulatory teams to: Define biomarker strategies for trial protocols Support dose escalation/expansion decisions Inform indication prioritization and patient enrichment strategies Translate multimodal model outputs and large-scale genomic analyses into clear, defensible recommendations for development teams and leadership. Contribute to cross-program biomarker standards, best practices, and reproducible analysis frameworks across the Pathos portfolio. Who you are Training PhD (or equivalent industry experience) in computational biology, cancer genomics, bioinformatics, or a related field. 5+ years' experience in a pharma or biotech company supporting oncology drug development in a translational, biomarker, or early clinical (Phase 1/2) setting. Technical & Domain Expertise Deep expertise in cancer genomics and transcriptomics, including hands-on experience with RNA-seq and DNA variant analysis in clinical contexts. Strong understanding of translational biomarkers across the drug development lifecycle, from hypothesis generation to clinical readouts. Experience analyzing biomarker data from interventional clinical trials, including response modeling, survival analysis, and subgroup discovery. Experience generating and validating genomic and multi-omic hypotheses across multiple drug modalities, including small molecules, monoclonal antibodies, bispecifics, and ADCs, with an understanding of how mechanism of action shapes biomarker strategy. Strong intuition for modality-specific biomarker requirements, such as target expression thresholds, pathway addiction, synthetic lethality, immune context, and resistance biology. Demonstrated ability to integrate genomic data with clinical endpoints and operational trial data. Familiarity with large oncology datasets (e.g., Tempus, TCGA, AACR GENIE) and applying them to inform development strategy. Fluency in R (and/or Python) with a strong emphasis on reproducibility and scientific rigor. Mindset & Collaboration Thinks like a drug developer, not just a data scientist—understands what makes a biomarker actionable in a real clinical program. Comfortable owning analyses that influence high-stakes decisions, including trial design and program prioritization. Excels at cross-functional collaboration with clinicians, translational scientists, and engineers. Able to clearly communicate complex genomic and biomarker findings to both technical and non-technical stakeholders. Location This is a hybrid role, requiring up to 3 days per week onsite, in our NYC Headquarters.

Full job record

Job ID	d7acb4e2a69100eee2531dee5d6589fa27ef6369
Org ID	25325165-9d82-45f6-8e64-74c33db17449
Source ID	2d66e9b5-1b63-475c-a03a-943980720722
Board ID	2d66e9b5-1b63-475c-a03a-943980720722
Provider	rippling
Provider Job Key	86e9bb79-5de8-4bc5-90ee-7886f8d04c87
Title	Senior Computational Biologist, Oncology
Normalized Title	—
Status	active
Active	yes
Location Text	New York City, NY, United States
Department	Computational Biology
Team	—
Employment Type	full_time
Workplace Type	on_site
Remote Policy	—
Country	United States
Region	NY
City	New York City
Salary Raw	USD 170000-210000 YEAR
Salary Min	170,000
Salary Max	210,000
Salary Currency	USD
Salary Period	year
Source URL	https://ats.rippling.com/pathos/jobs/86e9bb79-5de8-4bc5-90ee-7886f8d04c87
Apply URL	https://ats.rippling.com/pathos/jobs/86e9bb79-5de8-4bc5-90ee-7886f8d04c87
First Seen At	2026-05-29 07:13:53Z
Last Seen At	2026-06-06 19:47:28Z
Last Checked At	2026-06-06 19:47:28Z
Last Changed At	2026-06-06 19:47:28Z
Inactive At	—
Source Posted At	2026-01-09 19:39:20Z
Source Updated At	—
Raw Payload Uri	s3://job-postings-prod-raw-590183727216/raw/provider=rippling/board=pathos/date=2026-06-06/2026-06-06T19-47-27-796Z-028dedb1434ee889b96d1d2a4c6bc3c2f873f49fd400f2363c422a3c7900117a.json

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      "role": "<meta><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:14pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:justify;\"><b><strong style=\"color:rgb(0,0,0);font-size:14pt;white-space:pre-wrap;\">About the Role</strong></b></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:justify;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Pathos is building an AI-native biotech platform that turns real-world data and multimodal models into translational biomarker insights that directly shape drug development decisions—from early target validation through late-stage patient selection. We are redefining how oncology drug development is done: integrated, data-driven, and built from first principles.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:justify;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">As a Senior Computational Biologist, you will sit at the intersection of genomics, translational science, and clinical development. You will own and evolve genomics and biomarker pipelines that support our internal and in-licensed oncology assets, with a particular focus on mechanism-based biomarkers, response predictors, resistance biology, and patient stratification. Your work will span discovery through Phase 1/2 clinical trials, with direct impact on indication selection, dose expansion strategy, and Go/No-Go decisions.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:justify;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">You will generate and test biomarker hypotheses using deep genomic and multi-omic data derived from both external cohorts and Pathos-sponsored clinical trials, translating complex molecular signals into actionable insights for clinicians, program teams, and leadership. This role requires not just analytical excellence, but a strong understanding of how biomarkers are operationalized in real drug development settings.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:justify;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">If you want to apply cutting-edge computational and genomics methods to problems that directly determine how cancer drugs are developed and deployed, this is the place to do the most meaningful work of your career.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:justify;\"><b><strong style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Key Responsibilities</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Design, build, and maintain end-to-end translational genomics pipelines supporting oncology drug programs, including RNA-seq, DNA (SNV/CNV/structural variants), and multi-omic integration.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Generate and prioritize genomically grounded hypotheses tailored to different therapeutic modalities, including:</span></li></ul><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Target dependency and pathway activation for small molecules</span><br><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Expression, heterogeneity, and spatial context for mAbs, bispecifics, and ADCs</span><br><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Biomarkers of payload sensitivity, internalization, and resistance for ADC programs</span></li></ul><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Lead biomarker discovery and validation efforts across preclinical, translational, and clinical datasets, with a focus on:</span></li><li style=\"font-size:12pt;--listitem-marker-color:#000000;list-style:none;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><ul data-pattern=\"discCircleSquare\" data-depth=\"2\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin-left:0px;margin-right:0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:circle;\"><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Predictive and pharmacodynamic biomarkers</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">MOA and pathway activity signatures</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Resistance and escape mechanisms</span></li></ul></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Analyze and interpret clinical trial biomarker data (Phase 1/2), linking molecular profiles to response, durability, safety, and survival endpoints.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Partner closely with clinical, translational, and regulatory teams to:</span></li><li style=\"font-size:12pt;--listitem-marker-color:#000000;list-style:none;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><ul data-pattern=\"discCircleSquare\" data-depth=\"2\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin-left:0px;margin-right:0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:circle;\"><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Define biomarker strategies for trial protocols</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Support dose escalation/expansion decisions</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Inform indication prioritization and patient enrichment strategies</span></li></ul></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Translate multimodal model outputs and large-scale genomic analyses into clear, defensible recommendations for development teams and leadership.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Contribute to cross-program biomarker standards, best practices, and reproducible analysis frameworks across the Pathos portfolio.</span></li></ul><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:14pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:14pt;white-space:pre-wrap;\">Who you are</strong></b></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Training</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">PhD (or equivalent industry experience) in computational biology, cancer genomics, bioinformatics, or a related field.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">5+ years' experience in a pharma or biotech company supporting oncology drug development in a translational, biomarker, or early clinical (Phase 1/2) setting.</span></li></ul><h3 style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;line-height:1.6;font-size:12pt;font-weight:600;letter-spacing:0.25px;margin-top:14px;margin-bottom:4px;text-align:justify;padding-left:0px;\"><b><strong style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Technical &amp; Domain Expertise</strong></b></h3><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Deep expertise in cancer genomics and transcriptomics, including hands-on experience with RNA-seq and DNA variant analysis in clinical contexts.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Strong understanding of translational biomarkers across the drug development lifecycle, from hypothesis generation to clinical readouts.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Experience analyzing biomarker data from interventional clinical trials, including response modeling, survival analysis, and subgroup discovery.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Experience generating and validating genomic and multi-omic hypotheses across multiple drug modalities, including small molecules, monoclonal antibodies, bispecifics, and ADCs, with an understanding of how mechanism of action shapes biomarker strategy.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Strong intuition for modality-specific biomarker requirements, such as target expression thresholds, pathway addiction, synthetic lethality, immune context, and resistance biology.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Demonstrated ability to integrate genomic data with clinical endpoints and operational trial data.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Familiarity with large oncology datasets (e.g., Tempus, TCGA, AACR GENIE) and applying them to inform development strategy.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Fluency in R (and/or Python) with a strong emphasis on reproducibility and scientific rigor.</span></li></ul><h3 style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;line-height:1.6;font-size:12pt;font-weight:600;letter-spacing:0.25px;margin-top:14px;margin-bottom:4px;text-align:justify;padding-left:0px;\"><b><strong style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Mindset &amp; Collaboration</strong></b></h3><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Thinks like a drug developer, not just a data scientist—understands what makes a biomarker actionable in a real clinical program.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Comfortable owning analyses that influence high-stakes decisions, including trial design and program prioritization.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Excels at cross-functional collaboration with clinicians, translational scientists, and engineers.</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">Able to clearly communicate complex genomic and biomarker findings to both technical and non-technical stakeholders.</span></li></ul><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:14pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"color:rgb(0,0,0);font-size:14pt;white-space:pre-wrap;\">Location</strong></b></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:12pt;white-space:pre-wrap;\">This is a hybrid role, requiring up to 3 days per week onsite, in our NYC Headquarters.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:justify;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p>",
      "company": "<meta><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"font-size:12pt;white-space:pre-wrap;\">Drug development shouldn’t be guesswork, not when patients are waiting.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br><span style=\"font-size:12pt;white-space:pre-wrap;\">Pathos is building a next-generation biotech with AI at the core. Not as a feature, but as the operating system for how medicines get developed. We believe most drugs don’t fail because the science was wrong. They fail because they were tested in the wrong patients, with the wrong assumptions, in trials that couldn’t answer the real question: who benefits, and why?</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br><span style=\"font-size:12pt;white-space:pre-wrap;\">Pathos exists to change that. We’re building the largest foundation model in oncology and pairing it with proprietary AI systems, deep oncology expertise, and 200+ petabytes of multimodal data linked to patient outcomes, so we can make development decisions with more precision, much earlier.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br><span style=\"font-size:12pt;white-space:pre-wrap;\">This is not theoretical. We’re well-capitalized and have the leadership to build a generational company. We invest in and advance our own clinical-stage programs, using our AI platform to sharpen trial design, patient selection and biomarker strategy. So therapies reach the patients most likely to benefit, sooner.</span><br><br><b><strong style=\"font-size:12pt;white-space:pre-wrap;\">How We Build</strong></b><br><span style=\"font-size:12pt;white-space:pre-wrap;\">Pathos does not operate like a traditional biotech. There is no middle management. There are no layers of approval. The company is designed, from the ground up, around small teams of 2–4 subject-matter experts who each command hundreds of AI agents to do the work that used to require dozens of people.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br><span style=\"font-size:12pt;white-space:pre-wrap;\">Everyone builds. Everyone ships. Every function at Pathos — from clinical execution to asset selection to the foundation model itself — runs on this model. Our product velocity delivers meaningful outcomes in hours instead of weeks. This is not a future aspiration. It is how we operate today.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:12pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br><span style=\"font-size:12pt;white-space:pre-wrap;\">The people who thrive here are operators: deep experts who can specify what needs to happen, orchestrate AI agents to execute at scale, and make high-judgment calls that compound over time. If you have spent your career building and shipping AI systems at scale, this is the environment where that experience becomes a superpower.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p>"
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