Data Scientist Surgery Research Enterprise

Akron Children's Hospital•Akron, OH

13d•Hybrid

About The Position

The Data Scientist within the Surgery Research Enterprise at Akron Children’s Hospital advances the department’s research and analytics capabilities. Reporting to the Director of Research, this position supports clinical research, outcomes research, and advanced analytics across surgical divisions. The Data Scientist works independently, collaborates with investigators, and develops and leads research and data science projects from concept through analysis and dissemination. The role involves collecting, preparing, and analyzing complex data; developing and validating statistical and machine learning models; and communicating findings through visualizations, dashboards, and scholarly products. The Data Scientist also helps establish research and analytics priorities, cultivates internal and external partnerships, and shares expertise with the Surgery Research Enterprise and broader research community. This is a full-time, 40-hour-per-week hybrid position. The schedule is Monday through Friday, 8:00 a.m. to 4:30 p.m., with 6–12 onsite days per month.

Requirements

Master’s degree in data science, statistics, biostatistics, computer science, biomedical informatics, epidemiology, engineering, or a related quantitative field.
Minimum of 3 years of relevant experience in data science, healthcare analytics, clinical research, outcomes research, or a related field.
Experience working with complex healthcare, clinical, research, or administrative datasets.
Experience applying statistical techniques, machine learning, and advanced analytical methods to healthcare or clinical research data.
Expert-level skills in research, data science, clinical and/or research decision-making processes, techniques, and tools, such as Snowflake, Databricks, SAS, R, Python, and SQL.
Strong organizational and problem-solving skills, with attention to detail.
Excellent written and oral communication skills and good interpersonal skills; ability to interact professionally with a diverse group of staff and users.
Experience working independently and collaboratively with investigators and research teams to develop and execute research projects.

Nice To Haves

PhD or other relevant doctoral degree.
Demonstrated experience developing research questions, working with complex datasets, conducting advanced analyses, interpreting findings, and contributing to abstracts, presentations, manuscripts, or other scholarly products.
Experience independently developing and leading research or analytical projects.
Supervisory experience.

Responsibilities

Support development of advanced analytics and data science capabilities by gathering input from leaders, investigators, stakeholders, and peers, and contribute to a roadmap aligned with surgical research priorities.
Develop and maintain collaborative relationships with investigators, clinical leaders, research staff, and partners; understand the clinical and research context and strategic goals of surgical divisions.
Cultivate external partnerships with professional associations, communities, universities, research institutes, government agencies, solution providers, and vendors.
Collect and explore data from multiple sources, identify patterns and trends, and clean, transform, and validate data for research and analysis.
Design, develop, implement, and optimize predictive and prescriptive models using statistical techniques and machine learning algorithms.
Identify and engineer relevant dataset features in collaboration with clinical investigators and domain experts.
Develop, evaluate, validate, and refine statistical and machine learning models for accuracy, relevance, and effectiveness in clinical and research settings.
Create data visualizations and dashboards to communicate insights to technical and non-technical stakeholders, using Tableau, Power BI, or custom code.
Prioritize high-impact research and analytics use cases, gather feedback and support from partners and investigators, and make regular adjustments.
Identify research opportunities and independently develop and lead data science and outcomes research projects from concept through dissemination, including research-question development, study design, data identification, analysis, interpretation, and communication of findings.
Apply research and data science expertise; share successes and lessons learned; and teach or coach professionals in advanced analytics, data science, problem-solving methodologies, and related techniques.
Monitor industry, healthcare, surgical research, and data science trends and best practices, and identify opportunities to apply emerging methods to new research questions.