STARS Requisition number
94675BR
Posting Position Title
Biostatistician
Essential Duties
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.
Duration Type
Regular
Work Week
Standard (M-F equal number of hours per day)
University Job Title
Biostatistician
Worksite Address
300 Cedar Street
New Haven, CT 06510
Work Location
Medical School Campus
Drug Screen
No
Health Screening
No
Background Check Requirements
All candidates for employment will be subject to pre-employment background screening for this position, which may include motor vehicle, DOT certification, drug testing and credit checks based on the position description and job requirements. All offers are contingent upon the successful completion of the background check. For additional information on the background check requirements and process visit "Learn about background checks" under the Applicant Support Resources section of Careers on the It's Your Yale website.
Searchable Job Family
Research/Support
External Gateway Posting Date
02-May-2025
Total # of hours to be worked:
37.5
Position Focus:
The Department of Medicine, Division of Digestive Diseases at Yale School of Medicine, is recruiting one highly motivated bioinformatics/molecular epidemiology master level biostatistician to begin late Spring/Summer 2025. The successful candidate will work primarily with Dr. Louise Wang on identifying high risk individuals at risk of developing pancreatic cancer to undergo targeted screening and surveillance and improve survival of this deadly disease. Specific topics include, but are not limited to (i) developing statistical and machine learning methods for study designs and decision-making in early detection of pancreatic cancer (ii) establishing strategies where it would be cost-effective to screen and (iii) incorporating multi-omics data to better identify at-risk individuals beyond lifestyle and environmental approaches alone. Our research program has developed the methodological expertise to carry out analyses in the oldest and largest longitudinal electronic health record (EHR) in the US, the Veteran Affairs EHR for millions of individuals. Our group also leads efforts to improve early detection of pancreatic cancer within the VA Million Veteran Program, the largest mega biobank in the world, which links the necessary longitudinal clinical data with germline genetics, epigenetics, and metabolomics. This is a unique opportunity for someone who is interested in a collaborative, multidisciplinary environment (bioinformatics, epidemiology, genetics, gastroenterology, oncology) and interacting with physician-scientists and scientists with diverse experiences.
Preferred Education, Experience and Skills:
Proven experience with genetics data would be preferred. Proven experience in large-scale data analysis and biomedical informatics would be preferred.
Posting Disclaimer
The intent of this job description is to provide a representative summary of the essential functions that will be required of the position and should not be construed as a declaration of specific duties and responsibilities of the particular position. Employees will be assigned specific job-related duties through their hiring departments.
EEO Statement:
The University is committed to basing judgments concerning the admission, education, and employment of individuals upon their qualifications and abilities and seeks to attract to its faculty, staff, and student body qualified persons from a broad range of backgrounds and perspectives. In accordance with this policy and as delineated by federal and Connecticut law, Yale does not discriminate in admissions, educational programs, or employment against any individual on account of that individual’s sex, sexual orientation, gender identity or expression, race, color, national or ethnic origin, religion, age, disability, status as a special disabled veteran, veteran of the Vietnam era or other covered veteran.
Inquiries concerning Yale’s Policy Against Discrimination and Harassment may be referred to the Office of Institutional Equity and Accessibility (OIEA).
Compensation Grade
Clinical & Research
Compensation Grade Profile
Biostatistician (23)
Bargaining Unit
None - Not included in the union (Yale Union Group)
Supervisory Organization
Internal Medicine - Digestive Diseases
Time Type
Full time
Required Skill/Ability 1:
Masters in genomics, genetics, computational biology, epidemiology, bioinformatics, biostatistics, data science, informatics, or equivalent.
Required Skill/Ability 2:
Proficiency in computer programming (e.g., R, Python) and experience with high performance computing in Linux environment is required.
Required Skill/Ability 3:
Excellent communication, presentation and writing skills.
Note
Yale University is a tobacco-free campus
Wage Ranges
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Work Model
On-site
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