Position Title Data Scientist "Cancer Biology" for Academic Research Support Job Summary Tuskegee University Center for Biomedical Research (CBR) is seeking a highly skilled and motivated Data Scientist to join our research team at TU / CBR.
The successful candidate will play a pivotal role in advancing our understanding of cancer through thorough data analysis, utilizing expertise in epidemiology, biostatistics, and computational modeling, with a preference for R and python.
The Data Scientist will play a critical role in supporting students and Principal Investigators by providing expert analysis of large data sets, generating high-quality figures, and ensuring that data-driven insights are accessible to all members of our research community. Essential Job Duties
- Collaborate with research teams to understand their data analysis needs and goals.
- Apply advanced statistical techniques and machine learning algorithms to uncover patterns and insights within research data.
- Create compelling and informative visualizations and figures to effectively communicate research findings.
- Provide guidance on data collection methods and experimental design to ensure data quality and relevance.
- Assist with the interpretation of analysis results and provide recommendations for future research directions.
- Maintain up-to-date knowledge of data science trends, tools, and resources relevant to the academic research community.
- Ensure compliance with data privacy and security protocols when handling sensitive information.
- Contribute to research publications by providing data analysis expertise and generating publication quality figures.
Qualifications (Education, Experience and Specialized Training)
- Ph.D. or master’s degree in biomedical sciences with a focus in epidemiology, statistics, or bioinformatics, or equivalent doctoral degree in a field directly related to the position.
- A minimum of five (5) years of specialized experience in data analysis, with a focus on epidemiological and statistical methodologies.
Physical Demands Skills and Attributes
- Proficiency in conducting in-depth analysis using analytic and statistical software (e.g., SAS, SPSS, or STATA) to prepare, clean, analyze, and visualize data.
- Strong programming skills, particularly in R, with the ability to adapt and learn new languages as required.
- Excellent communication skills, both written and verbal, to effectively convey complex scientific concepts.