Chief Informatics Data Scientist

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Job Summary (Purpose and Function):

The Chief informatics Data Scientist is a role in the University of Miami Health System (UHealth) Information Technology (IT Department) and reports to the UHealth Chief Information Officer. They will play a pivotal role in planning, executing and delivering artificial intelligence, robotic process automation, machine learning, NextGen Medical Education and clinical research related data projects. The bulk of the work will be in machine learning/AI modelling, management and problem analysis, data exploration and preparation, data collection and integration, and turn over to the Chief Data Officer organization for operationalization. 

The Chief Informatics Data Scientist will be a key interface for the University, the UHealth Clinical Enterprise, MSOM NextGen Medical Education and Vice Provost for Research. 

Accountabilities (For Non-exempt Employees Include Percent of Effort): 

• Guide and inspire the organization about the business potential and strategy of artificial intelligence (AI)/data science 

• Identify data-driven/ML business opportunities 

• Collaborate across the business to understand IT and business constraints 

• Prioritize, scope and manage data science projects and the corresponding key performance indicators (KPIs) for success 

• Help to define and communicate governance principles 

• Understand new data sources and process pipelines, and catalog/document them 

• Acquire access to various databases, and other source systems such as SQL or graph databases. 

• Help to create data pipelines for more efficient and repeatable data science projects 

• Apply statistical analysis and visualization techniques to various data, such as hierarchical clustering, T-distributed Stochastic Neighbor Embedding (t-SNE), principal components analysis (PCA) 

• Generate hypotheses about the underlying mechanics of the business process 

• Test hypotheses using various quantitative methods 

• Display drive and curiosity to understand the business process to its core 

• Network with domain experts to better understand the business mechanics that generated the data 

• Apply various ML and advanced analytics techniques to perform classification or prediction tasks 

• Integrate domain knowledge into the ML solution; for example, from an understanding of financial risk, customer journey, quality prediction, sales, marketing 

• Testing of ML models, such as cross-validation, A/B testing, bias and fairness 

• Collaborate with ML operations (MLOps), data engineers, and IT to evaluate and implement ML deployment options 

• Integrate model performance management tools into the current business infrastructure 

• Implement champion/challenger test (A/B tests) on production systems 

• Continuously monitor execution and health of production ML models 

• Establish best practices around ML production infrastructure 

• Train other business and IT staff on basic data science principles and techniques 

• Train peers on specialist data science topics 

• Network with internal and external partners 

• Upskill yourself (through conferences, publications, courses, local academia and meetups). 

• Promote collaboration with other data science teams within the organization (if there is a decentralized data science practice). Encourage reuse of artifacts 

• Plans and coordinates educational programs within the Miller School of Medicine for the UHealth IT Informatics Track 

This list of duties and responsibilities is not intended to be all-inclusive and may be expanded to include other duties or responsibilities as necessary. 

Supervision Received: 

Position Reports directly to the Senior Vice President, Chief Information and Digital Officer

Minimum Qualifications (Essential Requirements): 

• Doctorate degree or Fellow of the Society of Actuaries (FSA) designation required 

• Candidates must have a specialization in ML, AI, cognitive science or data science