Job Description
SENIOR DATA SCIENTIST
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Seeking an expert‑level Data Scientist to lead state‑of‑the‑art research and develop advanced multimodal imaging models for our diagnostic intelligence platform. This role is designed for a senior practitioner with deep experience in medical imaging, radiology workflows, and machine learning research — someone capable of driving innovation from concept and academic rigor through to production‑grade deployment in clinical environments.
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Responsibilities
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- Lead ideation, research, and development of next‑generation models across CT, MRI, X‑ray, ultrasound, and multimodal fusion architectures.
- Architect and execute deep academic‑level research, including novel model designs, benchmarking, ablation studies, and scientific validation.
- Translate research outputs into production‑ready systems, ensuring reliability, scalability, and clinical relevance for real‑world diagnostic workflows.
- Build and oversee pipelines for dataset ingestion, cleaning, labeling, augmentation, multimodal alignment, and large‑scale imaging data management.
- Conduct expert‑level model evaluation, error analysis, robustness testing, and optimization for high‑performance inference.
- Ensure all workflows meet high regulatory standards, including data governance, auditability, reproducibility, and compliance expectations for medical AI.
- Collaborate closely with engineering, product, and clinical teams to deliver models that meaningfully advance diagnostic intelligence and clinical decision support.
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Required Experience
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- Master’s Degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Biomedical Engineering, or a closely related technical field.
- Expert proficiency in PyTorch, TensorFlow, Ultralytics YOLO, MONAI, and Hugging Face ecosystems.
- Demonstrated experience with medical imaging datasets, DICOM workflows, PACS systems, and radiology modalities.
- Hands‑on use of FiftyOne, Roboflow, Labelbox, V7, or Encord for dataset curation, annotation, and quality control.
- Proven ability to lead research initiatives and publish or present advanced imaging work at academic or industry venues.
- Strong background in segmentation, detection, multimodal architectures, and imaging‑specific preprocessing pipelines.
- Experience deploying models using Core ML, ONNX Runtime, NVIDIA TensorRT/DeepStream, or major cloud ML platforms (Azure, AWS, GCP).
- Solid engineering foundation in Python, GPU computing, Docker/Kubernetes, and scalable ML systems.
- Familiarity with regulatory frameworks relevant to medical AI, including data privacy, auditability, and reproducibility standards.
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Preferred
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- Prior collaboration with radiologists, imaging scientists, or clinical imaging teams.
- Experience building multimodal (vision + text) diagnostic or triage models.
- Experience working in a start-up company and small teams to develop big ideas that will have a global impact.
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