2. Develops and maintains collaborative relationships with investigators, clinical leaders, research staff, and partners. Builds an understanding of the clinical and research context and the strategic goals of the surgical divisions.

3. Cultivates external partnerships with professional associations, communities, universities, research institutes, government agencies, and solution providers or vendors to advance research and analytics objectives.

4. Collects and explores raw data from multiple sources to identify patterns, trends, and potential insights. Cleans, transforms, and validates data to ensure its quality and suitability for research and analysis.

5. Designs, develops, implements, and optimizes predictive and prescriptive models using statistical techniques and machine learning algorithms to improve accuracy and performance.

6. Identifies and engineers relevant features from datasets to strengthen model predictive power. Collaborates with clinical investigators and domain experts to extract meaningful features that improve model effectiveness.

7. Develops, evaluates, validates, and refines statistical and machine learning models to ensure accuracy, relevance, and effectiveness in clinical and research settings. Applies advanced analytical techniques to support clinically meaningful surgical research.

8. Creates compelling data visualizations and dashboards that communicate insights and findings effectively to technical and non-technical stakeholders using Tableau, Power BI, or custom code.

9. Prioritizes a limited number of high-impact research and analytics use cases. Collaborates with key partners and investigators to gather feedback, secure support, and make regular adjustments.

10. Identifies research opportunities and independently develops and leads data science and outcomes research projects from concept through dissemination, including research question development, study design, data identification, analysis, interpretation, and communication of findings.

11. Applies research and data science expertise and shares success stories and lessons learned with the Surgery Research Enterprise and broader research community. Teaches or coaches professionals in advanced analytics, data science, problem-solving methodologies, and related techniques to support professional development.

1. Strong organizational and problem-solving skills required, with an emphasis on attention to detail.
2. Excellent written and oral communication skills, along with good interpersonal skills.
3. Professional interaction with a diverse group of staff and users.
4. Experience working independently and collaboratively with investigators and research teams to develop and execute research projects.
5. Experience working with complex healthcare, clinical, research, or administrative datasets.
6. Expert-level skills in research, data science, clinical and/or research decision-making processes, techniques, and tools (e.g., Snowflake, databricks, SAS, R, Python, SQL, etc.).
7. Experience applying statistical techniques, machine learning, and advanced analytical methods to healthcare or clinical research data required.
8. Demonstrated experience developing research questions, working with complex datasets, conducting advanced analyses, interpreting findings, and contributing to abstracts, presentations, manuscripts, or other scholarly products preferred.

Education and Experience

1. Education: Master's degree in data science, statistics, biostatistics, computer science, biomedical informatics, epidemiology, engineering, or a related quantitative field required. PhD or other relevant doctoral degree preferred.

2. Licensure: NA

3. Certification: NA

4. Years of relevant experience: Minimum of 3 years of relevant experience in data science, healthcare analytics, clinical research, outcomes research, or a related field required. Experience independently developing and leading research or analytical projects strongly preferred.

5. Years of supervisory experience: Preferred but not required.