The Cleveland Clinic’s Research and Innovation and Education Institute is focused on advancing medical knowledge and patient care through research, education, and translating scientific discoveries into practical applications. This role will contribute to the growth of DDI Research and support the advancement of NCI trials and other research initiatives.
Requirements
- Highly proficient in programming skills in languages such as SAS, SQL, SPSS, R, Python, MATLAB or similar
- Experience in machine learning and data analytics
- Experience with Python and/or R
Responsibilities
- Utilize methods in Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL) and Natural Language Processing (NLP) to design and implement data solutions.
- Build complex predictive models, mixed models, attribution models, and other mathematical or statistical models as required, using appropriate modeling tools.
- Develop novel algorithms and high-level data analyses that integrate implementation, visualization and database management of multi-dimensional clinical or biological datasets.
- Pull, clean and manage data from multiple sources and databases to support ongoing research and machine learning initiatives.
- Collaborate closely with Dr. Li’s team and the Data Lab to process research data, including projects on cancer diagnostics and other clinical studies.
- Contribute to both research and innovative projects, such as building platforms that streamline clinical workflows (e.g., reading and summarizing faxes in EPIC).
- Support machine learning models that continuously ingest data to improve predictive accuracy and algorithm performance.
Other
- Serve as a team lead to the Principal Investigator, providing training, mentoring and instruction to other lab members on tools and data analysis techniques.
- Communicate and present research findings to the Principal Investigator, the broader research community and professional forums.
- Work collaboratively in a team-oriented environment, contributing to the growth and success of DDI Research initiatives.
- Bachelor’s Degree in Statistician, Actuarial Science, Econometrics, Physics, Biostatistics, Computer Science, Applied Mathematics, Engineering, Business Analytics, Economics, Finance or related field and six years of related experience, working with statistical modeling, machine learning or complex data analysis OR Master’s degree in related field may offset 2 years of experience OR PhD in related field may offset 3 years of experience
- Excellent communication and presentation skills
- Project Management skills
- Healthcare or clinical background
