Principal Data Scientist

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Cloud computing, Scala Programming, Machine learning techniques, Data science techniques, MATLAB Programming, PyTorch, TensorFlow, R Programming

Job Description

At Boston Scientific, we’ll give you the opportunity to harness all that’s within you by working in teams of diverse and high-performing employees, tackling some of the most important health industry challenges. With access to the latest tools, information and training, we’ll help you in advancing your skills and career. Here, you’ll be supported in progressing – whatever your ambitions.

About the role:

Data Scientist will work with a small team of data scientists developing and deploying Deep Learning models to interpret biologic signals on ambulatory patients to improve patient outcomes. The team has developed a large volume of diverse and accurate data for training and validation and works closely with experts in this domain.

Your responsibilities will include:

• Develop models and infrastructure to interpret biologic signals and other business data
• Validation and documentation of models for production deployment
• Support production deployment and monitoring of models
• Publishing research in support of business needs
• Developing and documenting intellectual property

Required qualifications:

• PhD in Computer Science, Biomedical Engineering, or related field of study with a minimum of 2 years' industry experience OR Master of Science with a minimum of 5 years' industry experience in Analytics OR Bachelor of Science with a minimum of 10 years' industry experience in analytics
• Minimum of 4 years' experience with Python
• Demonstrated cross function teamwork in a technically demanding environment

Preferred qualifications:

• ECG / PPG device experience
• Experience with deep learning toolkits (Tensorflow, PyTorch, Keras, etc)
• Experience with Azure Cloud technologies (Azure Storage, Azure Service Bus, etc)
• Experience with containerization technologies (Kubernetes, Docker, Helm, etc)
• Demonstrated use of source control tools (Git, etc)
• Practical experience developing and deploying software
• Experience with regulatory validation processes for software as a medical device