The Yale/Yale New Haven Hospital Center for Outcomes Research and Evaluation (CORE) is a leading national outcomes research center dedicated to transforming healthcare for the betterment of people and society by leveraging data, analytics, and technology. We have assembled a talented, multidisciplinary group who are committed to developing solutions to the practical needs of medicine and healthcare. Our organization combines the highest academic ideals with a pragmatic approach that emphasizes the production of useful knowledge. We are distinguished by our creativity, dedication, experience, and skills – and our commitment to having our work make a tangible difference to patients, the public, and society.
CORE is seeking a Biostatistician who will work under the direction of the Director of Data Management and Analytics to provide comprehensive statistical support to multiple contract and grant funded health outcomes projects.
The Biostatistician will perform a variety of duties involving the application of statistical and/or machine learning methods to the analysis of health outcomes data. They will work as part of a project team to: provide input in the design and analysis of research questions, assist in drafting analytic plans, prepare manuscripts/technical reports, and present/communicate statistical interpretations of data for multiple audiences with various technical backgrounds. The Biostatistician will also process/clean data, conduct analyses, and clearly document and disseminate findings. As part of a project team, they collaborate with a group of multidisciplinary team members to achieve project goals.
1. Evaluates and analyzes data using accepted statistical and biostatistical techniques.
2. Investigates, analyzes, and evaluates complex statistical and programming problems. Determines proper methodology, testing standards, and evaluation processes for research projects. Recommends and develops statistical approaches for use in analyses.
3. Prepares analysis plans and writes detailed specifications for analysis files, consistency checks, tables, and figures; communicates with clients regarding statistical analysis issues.
4. In collaboration with research investigators, contributes to the design of research studies, develops analytical plans, conducts statistical analysis and interpret the results.
5. Ensures the integrity of databases used in analyses through development of essential data cleaning and checks, and data back-ups.
6. Plans statistical programming activities and schedules to provide investigators with time frames for projects.
7. Recommends and develops statistical approaches by testing and prototyping.
8. Organizes and creates documents and tables related to datasets; communicates with data sources about data accuracy and data dictionary.
9. May perform other duties as assigned.
Required Education and Experience
Master’s Degree in Biostatistics, Statistics or relevant field. Two years of experience; or equivalent combination of education and experience.
Required Skill/Ability 1:
Coursework in generalized linear, generalized linear mixed, survival, and Bayesian models and/or machine learning methods.
Required Skill/Ability 2:
Knowledge and related work experience utilizing statistical programming (SAS/R/Python) for generalized linear, generalized linear mixed, survival, and Bayesian models and/or machine learning applications.
Required Skill/Ability 3:
Well-developed analytical, organizational, oral and written communication skills. Demonstrated strong ability to communicate technical ideas and results to non-technical customers in written and verbal formats.
Required Skill/Ability 4:
Ability to work in a multidisciplinary team environment and manage/ prioritize multiple projects to ensure their quality and on-time delivery.
Required Skill/Ability 5:
Reliable, professional and flexible. Careful and thorough while adaptable and innovative in conducting statistical analysis.
Preferred Education, Experience
Previous work experience as a statistician for healthcare services or medical field projects. Experience with healthcare data, particularly Medicare or other insurance claims data, clinical registry, Electronic Health Records (EHR), or patient reported outcomes for statistical analysis highly preferred.