Role Overview
Analyzes diverse and complex datasets using artificial intelligence, machine learning, and statistical methods to generate insights that advance patient health outcomes and inform clinical strategies. This position collaborates closely with healthcare providers, data specialists, and external collaborators to design and implement analytical tools tailored for use in clinical environments.
Key Responsibilities
- Applies data science methodologies to extract meaningful patterns from structured and unstructured data sources to address real-world clinical and operational challenges.
- Develops and refines scripts or software components to support data processing, transformation, and analysis workflows.
- Performs modeling tasks such as regression, clustering, classification, and pattern detection using advanced statistical and machine learning techniques.
- Interprets analytical results and contributes to technical and non-technical reporting, ensuring findings are accessible to stakeholders without data expertise.
- Supports data requesters by clarifying dataset characteristics, offering guidance on data quality, and recommending improvements.
- Communicates technical outcomes clearly to clinical and administrative audiences, enabling informed decision-making at the point of care.
- Works within defined project parameters to deliver timely, accurate, and reproducible analyses.
Qualifications
Required
- Bachelor’s degree in computer science, mathematics, engineering, health informatics, or a related quantitative discipline.
- At least three years of professional or research experience applying data science techniques.
- Proven experience building predictive models using machine learning, statistical modeling, or data mining.
- Proficiency with analytical tools and methodologies, including statistical software and modeling frameworks.
- Strong problem-solving skills with a focus on continuous improvement and structured analysis.
- Ability to manage multiple concurrent projects and shifting priorities effectively.
- Excellent communication abilities and a service-oriented mindset.
- Familiarity with data exploration, visualization, and modeling tools.
Preferred
- Advanced degree (Master’s or PhD) in a quantitative or health-related field.
- One or more years of data-focused experience for candidates holding graduate degrees.
Technical Environment
Utilizes AI, deep learning, neural networks, decision trees, clustering algorithms, probability theory, operations research, and statistical modeling to process and interpret large-scale healthcare data.
Work Environment
This role operates in a hybrid model, with team members distributed across multiple U.S. campuses and international locations, allowing for flexible work arrangements. Primary hubs include metropolitan and Midwestern clinical sites.
Benefits and Development
- Comprehensive medical, dental, and vision coverage with flexible plan options.
- Pre-tax savings accounts (HSA, FSA) and a robust retirement program.
- Support for continuing education, professional growth, and career progression.
Compensation
Offers competitive pay aligned with experience and market standards.
Commitment to Inclusion
This organization is an equal opportunity employer. Employment decisions are made without regard to race, color, religion, gender identity, sexual orientation, national origin, veteran status, or disability. The organization complies with federal work authorization verification requirements through participation in E-Verify.
