Senior Data Scientist

Summary

Join Northwestern Medicine as a Senior Data Scientist in Chicago, IL, and build machine learning models, lead requirements gathering, and provide technical advice. Responsibilities include data extraction, model development, and team training. A Master's degree in a related field plus 5 years of experience or a Ph.D. plus 3 years of experience is required. Proficiency in SQL, Python, and a deep learning library is essential. Northwestern Medicine offers competitive benefits, including 401(k) matching and lifecycle benefits.

Requirements

• Master’s in Machine Learning, Computer Science, Engineering, Math, Physics, or a related field plus 5 years of relevant experience with machine learning, a focus on model building, and analysis of outcomes and model deployment in Data Scientist- Innovation, Graduate Assistant, or a related position
• Doctorate (Ph.D.) in Machine Learning, Computer Science, Engineering, Math, Physics, or a related field plus 3 years of relevant experience with machine learning, a focus on model building, and analysis of outcomes and model deployment in Data Scientist- Innovation, Graduate Assistant, or a related position
• Experience running projects from inception to deployment
• Familiar with the product development lifecycle
• Proficiency in SQL, Python, and a deep learning library like PyTorch
• Experience with machine learning algorithms and frameworks like scikit-learn (sklearn) or SparkML for building and evaluating models
• Professional experience using cloud platforms like Azure for scalable data processing and model deployment
• Experience with software engineering principles around testing, code reviews, and deployment
• Experience utilizing problem-solving skills to analyze complex problems, break them down into manageable tasks, and develop effective solutions
• Experience working effectively in interdisciplinary teams, including clinicians, to understand their needs and translate them into data-driven solutions
• Experience leading and influencing cross-functional teams
• Experience building and growing relationships with stakeholders to ensure alignment and successful implementation of data-driven solutions
• Experience with feature engineering and selection methods to improve model performance
• Experience mentoring on topics like programming, deployment, maintenance, project lifecycle, and working with stakeholders

Responsibilities

• Build models by executing predefined experiments and templated code within the standard model development paradigm (25%)
• Data extraction and preparation for use in solution building (20%)
• Lead requirements gathering efforts using your technical and product acumen to identify solutions to stakeholder problems (25%)
• Provide technical and infrastructural advice on model builds, solution design, and requirements (15%)
• Help train the rest of the team in product lifecycle management, solution design, technical tool usage, and machine learning specifics (15%)

Benefits

• 401(k) matching
• Lifecycle benefits