About the position
The Senior Data Scientist reflects the mission, vision, and values of NM, adheres to the organization’s Code of Ethics and Corporate Compliance Program, and complies with all relevant policies, procedures, guidelines and all other regulatory and accreditation standards. Northwestern Medicine Information Services drives innovative, high-value solutions to transform health care. We are committed to supporting the relentless pursuit of better medicine by providing exceptional service to our patients and guests as well as internal clients across the organization. To ensure excellence, our team goes to extraordinary lengths to ensure that our systems work together seamlessly. Northwestern Medicine understands that technology plays an integral role in shaping the future of health care. Information Services strategically supports the organization by enabling digital solutions by leveraging capabilities such as AI, automation, and rollout of advanced cyber controls that support digital transformation strategies, implementing advanced technologies in clinical and administrative areas, and further developing the end user support model to help enhance modern infrastructure.
Responsibilities
- Work with stakeholders to design, build, and evaluate solutions to business and clinical problems within the organization.
- Use data, statistics, and machine learning tools to construct solutions that meet the requirements of the problem and deliver those solutions to make a tangible impact.
- Collaborate with experts to understand and solve problems.
- Bring a product mindset to a technical field to design solutions that deliver value and can be maintained.
- Help train the rest of the team to have that same mindset.
- Conduct research and development as well as prototyping advanced technology solutions to enhance medical training, improve quality of care, and enable timely interventions for pulmonary and thoracic patients.
- Contribute to the development of advanced technologies that enable the use of medical data across a variety of disciplines and modalities.
Requirements
- Master's degree or equivalent experience in CS, Engineering, Math, Physics, or a related field.
- At least 5 years of experience in machine learning with a focus on model building, analysis of outcomes, and model deployment.
- Professional experience using cloud platforms like Azure for scalable data processing and model deployment.
- Proficiency in SQL, Python, and a deep learning library like PyTorch.
- Strong problem-solving skills. Able to analyze complex problems, break them down into manageable components, and develop effective solutions.
- Works well with ambiguity. Can navigate a complex problem with little guidance and still deliver results.
- Strong stakeholder management skills. Experience building and growing relationships with stakeholders to ensure alignment and successful implementation of data-driven solutions.
- Able to mentor the rest of the team on topics like programming, deployment, maintenance, project lifecycle, working with stakeholders, etc.
- Systems level thinking. Ability to think about how a solution will be used and identify other components that need to be built or integrated.
- Experience running projects from inception to deployment. Familiar with the product development lifecycle.
- Experience leading and influencing cross-functional teams.
- Product mindset. Able to identify and design solutions that solve a family of problems when relevant.
Nice-to-haves
- PhD in Computer Science, Engineering, Mathematics, or a related field.
- Knowledge of audio processing techniques and algorithms.
- Experience collecting, preprocessing, and augmenting audio datasets, converting raw audio into spectrogram images.
- Apply techniques like data augmentation (noise addition, time shifting, etc.) to enhance model robustness.
- Strong understanding of image processing techniques and algorithms.
- Experience with traditional and modern computer vision techniques (e.g. object detection, image segmentation, image, and feature extraction).
- Domain knowledge in healthcare. Understanding of healthcare terminology, workflows, and challenges, enabling effective collaboration with clinicians and healthcare professionals.
- Health care data integration experience (PHI/HIPAA, HL7 FHIR).
- Familiarity with FDA regulation for software as a medical device.
- Experience making strategy decisions for a team while considering short- and long-term impacts.
Benefits
- Tuition reimbursement
- Loan forgiveness
- 401(k) matching
- Lifecycle benefits
