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.
CORE is seeking a senior level Statistician II 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 Statistician II 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 statistical lead of a project team to: provide input in the design and analysis of research questions, lead or assist in drafting analytic plans, prepare manuscripts/technical reports, and present/communicate statistical interpretations of data for multiple audiences with various technical backgrounds. The Statistician II 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. Develops operational procedures for collection, editing, verification, and management of statistical data.
2. Develops and implements relevant statistical programs to incorporate data from multiple projects.
3. Designs comprehensive relational databases with working knowledge of the scientific applications impacting on the data analysis and reporting.
4. Assists faculty and other research professionals with the formulation and description of appropriate statistical methods.
5. Evaluates research studies and recommends statistical procedures to analyze the data.
6. Carries out comprehensive statistical analysis for a broad spectrum of types of data and types of studies.
7. Integrates the research methodologies of multiple projects into bio-statistical analyses.
8. Prepares reports summarizing the analysis of research data, interpreting the findings and providing conclusions and recommendations.
9. Presents talks, seminars, or other oral presentations on the methodology and analysis used in scientific studies.
10. Assists investigators in preparation of research grant applications by writing research methods sections pertaining to acquisition, analysis, relevance and validity of data.
11. Participates in the preparation of manuscripts that are submitted for peer reviewed publication.
12. May supervise and provide training for lower level or less experienced employees.
13. May perform other duties as assigned.
Required Education and Experience
Master’s Degree in Biostatistics, Statistics, or relevant field. Four years of experience, or an 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:
Advanced 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 and Skills:
PhDs encouraged to apply. Previous work experience as the primary 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.