At Q Bio we are transforming healthcare by combining AI Physics and Biology to automate the physical exam making preventive personalized care accessible to all. We are hiring a Senior Scientist focused on predictive modeling and biomarker analytics.
The Role:
We are looking for a hands-on senior applied scientist or engineer with experience in predictive modeling biomarker stratification and multi-modal data integration. You will be responsible for building models that uncover patterns correlations and risk signatures across imaging bloodwork and genomics turning Q Bios deep datasets into actionable health insights. This role is highly technical and execution-focused: you will design prototype validate and help produce predictive models in collaboration with our engineering product and clinical teams.
What You Will Do:
- Develop and deploy predictive models and risk stratification frameworks linking imaging lab and genomic biomarkers.
- Implement pattern recognition and feature correlation pipelines to detect early biological changes across systems (e.g. neurometabolic musculoskeletalmetabolic).
- Translate scientific hypotheses into computational models that can be tested and validated using Q Bios internal datasets.
- Integrate models into the Gemini and Constellation platforms for visualization and clinical interpretation.
- Collaborate with engineers on scalable production-ready codebases and model deployment pipelines.
- Leverage Q Bios diverse datasets and external cohorts for model validation.
- Partner with clinical and regulatory stakeholders to ensure model robustness and alignment with submission requirements.
What You Will Bring:
- MS or PhD in Biomedical Engineering Computational Biology Data Science or related quantitative discipline.
- 6 years of experience building and validating machine learning or predictive models in biomedical or imaging domains.
- Advanced proficiency in Python scientific computing and ML frameworks (scikit-learn PyTorch TensorFlow).
- Deep understanding of statistical learning data normalization and model interpretability in heterogeneous biomedical datasets.
- Track record of delivering production-quality analytical models or pipelines (not just prototypes).
- Excellent communication skills and the ability to collaborate with cross-functional teams (engineering clinical product).
Preferred
- Experience integrating quantitative imaging data (MRI qMRI CT) with biochemical genomic or clinical biomarkers.
- Familiarity with biological pathway modeling or multi-omics integration.
- Exposure to regulated environments (FDA submissions IRB-approved studies clinical validation).
- Demonstrated ability to move from concept to deployment in small fast-paced teams
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
Required Experience:
Senior IC
At Q Bio we are transforming healthcare by combining AI Physics and Biology to automate the physical exam making preventive personalized care accessible to all. We are hiring a Senior Scientist focused on predictive modeling and biomarker analytics. The Role:We are looking for a hands-on senior appl...
At Q Bio we are transforming healthcare by combining AI Physics and Biology to automate the physical exam making preventive personalized care accessible to all. We are hiring a Senior Scientist focused on predictive modeling and biomarker analytics.
The Role:
We are looking for a hands-on senior applied scientist or engineer with experience in predictive modeling biomarker stratification and multi-modal data integration. You will be responsible for building models that uncover patterns correlations and risk signatures across imaging bloodwork and genomics turning Q Bios deep datasets into actionable health insights. This role is highly technical and execution-focused: you will design prototype validate and help produce predictive models in collaboration with our engineering product and clinical teams.
What You Will Do:
- Develop and deploy predictive models and risk stratification frameworks linking imaging lab and genomic biomarkers.
- Implement pattern recognition and feature correlation pipelines to detect early biological changes across systems (e.g. neurometabolic musculoskeletalmetabolic).
- Translate scientific hypotheses into computational models that can be tested and validated using Q Bios internal datasets.
- Integrate models into the Gemini and Constellation platforms for visualization and clinical interpretation.
- Collaborate with engineers on scalable production-ready codebases and model deployment pipelines.
- Leverage Q Bios diverse datasets and external cohorts for model validation.
- Partner with clinical and regulatory stakeholders to ensure model robustness and alignment with submission requirements.
What You Will Bring:
- MS or PhD in Biomedical Engineering Computational Biology Data Science or related quantitative discipline.
- 6 years of experience building and validating machine learning or predictive models in biomedical or imaging domains.
- Advanced proficiency in Python scientific computing and ML frameworks (scikit-learn PyTorch TensorFlow).
- Deep understanding of statistical learning data normalization and model interpretability in heterogeneous biomedical datasets.
- Track record of delivering production-quality analytical models or pipelines (not just prototypes).
- Excellent communication skills and the ability to collaborate with cross-functional teams (engineering clinical product).
Preferred
- Experience integrating quantitative imaging data (MRI qMRI CT) with biochemical genomic or clinical biomarkers.
- Familiarity with biological pathway modeling or multi-omics integration.
- Exposure to regulated environments (FDA submissions IRB-approved studies clinical validation).
- Demonstrated ability to move from concept to deployment in small fast-paced teams
We may use artificial intelligence (AI) tools to support parts of the hiring process such as reviewing applications analyzing resumes or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed please contact us.
Required Experience:
Senior IC
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