Senior Data Scientist I

Role Overview
Develop AI/computer vision methodologies for whole slide image analysis in nonclinical drug development.
Design and implement algorithms for anomaly detection, segmentation, and classification to enable accurate, efficient AI-assisted digital pathology readouts.
Required skills include Python/C++, TensorFlow/PyTorch, image processing libraries, deep learning (including large vision models), and experience analyzing large-scale biomedical datasets.

Responsibilities
- Conceive, design, and implement technical ideas integrating, visualizing, and analyzing large biomedical image data.
- Build expertise in storage/transfer/integration/visualization/analysis of large data; lead software development, data warehousing, statistics, and AI/ML.
- Apply biomedical/pharmaceutical knowledge to deliver agile, impactful, cost-effective solutions.
- Work autonomously; initiate meaningful investigations.
- Direct mentorship; author publications and presentations; present at external conferences.
- Follow applicable corporate/divisional policies (e.g., code of conduct, safety, GxP compliance, data security).

Qualifications
- BS with typically 10 years, or MS with typically 8 years, or PhD (CS, biomedical engineering, pathology informatics, or related) emphasizing computer vision/ML.
- Scientific initiative/creativity; independently design/execute experiments and interpret data.
- Project management; resolve key project hurdles; scientific writing.
- Global mindset; strong English communication.

Preferred
- Unsupervised/weakly supervised CNN/RNN (e.g., GANs, contrastive learning), multiple instance learning, transformer models.
- Foundation model expertise; digital pathology software experience (e.g., Visiopharm, HALO, Patholytix).
- MLOps principles.

Benefits
- Paid time off; medical/dental/vision insurance; 401(k) (eligible employees); short-term incentive program eligibility.