Business Intelligence Architect - Internal Medicine

Work closely with clinical research and data analysis teams to gather, analyze, and interpret complex healthcare data sets under supervision from senior data scientists and research managers. Extract relevant data from relational database systems in clinical data warehouses using SQL, apply expertise in statistical analysis by using R, Python, or similar tools, and contribute to research studies at the University of Iowa Carver College of Medicine and the Iowa City Veteran Affairs Medical Center., * Utilize Python, R, or SAS (or similar programming languages) to clean, preprocess, analyze, and visualize large datasets to extract meaningful insights.

• Implement reproducible analysis pipelines, ideally using Git/GitHub-based collaborative development workflows, adhering to open-science practices.
• Perform advanced data analysis techniques.
• Relational Database Expertise: Design and optimize SQL queries to retrieve, manipulate, and transform data from relational databases and other data sources.
• Perform advanced modeling including multi-task learning, sequence/time-series forecasting, survival/event-time analysis, and risk stratification for health services research studies.
• Conduct high-dimensional causal inference and mediation analysis to map pathways linking exposures, confounders, and clinical mediators to health outcomes.
• Evaluate and audit clinical ML and NLP models for calibration, uncertainty estimation, interpretability, and subgroup fairness.
• Apply advanced statistical and machine learning techniques to develop longitudinal predictive models and clinical algorithms.
• Work closely with health services investigators on the initiation of new research projects and the development of study design and analytic plans for grant proposals.
• Prepare scientific manuscripts and reports jointly with a team of health services investigators.
• Ensure data quality and integrity through data validation, cleaning, and error detection.
• Stay updated on the latest developments in data science, statistical analysis, and relevant technologies.
• Mentor junior-level analysts, serve as a technical lead, and drive technology roadmaps for data operations leveraging your organizational leadership experience.

• A Master’s degree or an equivalent combination of education and experience is required.
• Complex Data Analysis: Substantial experience in complex data analysis using software/languages such as R, Python, or similar is required.
• Advanced Statistical Modeling: Mastery of advanced statistical modeling such as generalized linear regression, mixed-effect generalized linear regression, and Cox regression models is required.
• Database Optimization: In-depth knowledge of relational database systems and proficiency in SQL query optimization is required.
• Core Competencies: Excellent analytical and problem-solving skills are required., * Ph.D. completed or near completion in a quantitative field is preferred
• Trial Design & Causal Inference: Experience in trial design and/or causal inference and mediation methodology is desired.
• Machine Learning: Experience with machine learning, predictive modeling, and advanced frameworks (e.g., multi-task learning, deep learning) is desired.
• Text Analytics: Experience with text classifications and natural language processing is desired.
• Collaborative Mindset: The ability to work both independently and collaboratively in a fast-paced, multi-disciplinary research team is desired.
• Supervision & Leadership: The ability to provide functional and/or administrative supervision of staff and mentor junior-level analysts is desired., Successful candidates will be required to self-disclose any conviction history and will be subject to a criminal background check and credential/education verification. Up to 5 professional references will be requested at a later step in the recruitment process.