Senior Data Scientist, Analytics & Informatics

Responsibilities

• Lead Complex Modeling & Research
• Conceptualize and implement complex statistical and machine learning models to evaluate health outcomes, cost-effectiveness, and other critical business needs.
• Collaborate with clinical faculty and subject matter experts to identify research hypotheses and conduct rigorous analyses using large real-world healthcare data sets.
• Mentorship & Team Leadership
• Provide guidance and mentorship to junior and mid-level Data Scientists, reviewing their work, offering technical support, and promoting best practices.
• Facilitate knowledge-sharing sessions to encourage professional growth, foster collaboration, and maintain high-quality standards within the team.
• Project & Stakeholder Management
• Independently manage large-scale data science projects, including scoping, planning, execution, monitoring, and stakeholder communication.
• Collaborate cross-functionally to align data-driven initiatives with strategic objectives, ensuring timely delivery of insights and solutions that address business challenges.
• Serve as a trusted advisor by proactively identifying opportunities to apply advanced analytics for improved clinical and financial outcomes.

Data Extraction & Analysis

• Review data extraction processes using electronic medical records (EMRs) and additional healthcare data sources to generate high-fidelity datasets for analysis.
• Design and maintain end-to-end analytical pipelines, including pre-processing, validation, feature engineering, model development, and performance monitoring.

Advanced Analytics & Methodology

• Apply observational study designs, advanced causal inference methods (e.g., propensity scores, handling missing data), and statistical techniques relevant to healthcare research.
• Explore, evaluate, and integrate emerging technologies (e.g., AI/ML frameworks, cloud-based tools) to continuously improve modeling efficiency and scalability.

Communication & Knowledge Translation

• Present findings through clear, compelling visualizations and narratives that resonate with both technical and non-technical audiences, including senior executives.
• Contribute to manuscripts, abstracts, posters, and conference presentations, demonstrating the impact of advanced analytics in healthcare.

Continuous Improvement & Thought Leadership

• Stay abreast of industry trends, research advances, and best practices in data science and healthcare analytics.
• Proactively share insights and implement innovative analytics methods to maintain UPMCE's position as a thought and technical leader in the healthcare data science space.

Qualifications

• Master's in health economics, data science, statistics, computer science or related field, with at least 5 years of experience in developing, implementing and overseeing models related to health services/ outcomes research and medical information programs or related work experience; OR, PhD/MD with training or equivalent terminal degree in health economics, data science, statistics, computer science or related field, with at least 3 years of experience in developing, implementing and overseeing models related to health services/outcomes research and medical information programs or related work experience.
• Comparable combination of education and experience will be considered in lieu of the above stated qualifications.
• Demonstrated expertise in relevant applied analytical methods in healthcare (payor/provider).
• Demonstrate prior independent application of data science methods specifically to healthcare industry data.
• Ability to leverage cutting-edge data science experience from other industries (e.g., population segmentation, risk analysis, optimization analysis, real-time analytics) to advance healthcare analytics will be strongly considered in lieu of health care experience.