Senior Data Scientist

SENIOR DATA SCIENTIST
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.
Responsibilities
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.
Required Experience
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.
Preferred
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.

Work arrangement
Yes