Description: Applies scientific methodology to conceptualize, propose, and implement appropriate methodologies for statistical analyses. Maintains and updates centralized research awards database. Assists with grant preparations and clinical trial budgets. Develops and validates reporting data, validates data subsets of funding data, and facilitates quality control procedures to ensure data accuracy.
The Department of Orthopedics at the University of Pittsburgh is seeking a highly motivated Master's Level Biostatistician to join a multidisciplinary team of physicians dedicated to treating musculoskeletal conditions. This position will collaborate and advise faculty on the appropriate statistical methods and ultimately apply them to research design and outcomes analysis. The analyst will have opportunities for authorship on publications stemming from their work and will play a key role in producing and sharing the results the broader scientific community.Education/Experience • Master's Degree in related field of biostatistics, data science, or epidemiology. • 0 years required (1-3 years preferred) of biostatistical consulting experience. Competencies • Strong knowledge of statistical software such as SAS, R, or STATA.• Excellent written and verbal communication skills.• Intermediate proficiency in data preparation, descriptive analyses, comparative statistics, and advanced statistical modeling.• Possess ability to interpret technical medical data and generate sound recommendations to support clinical research efforts.• Ability to work independently and as part of a team.• Demonstrate good organization skills, effective time management, and the ability to manage several concurrent tasks.• Maintain a team-oriented approach and possesses the ability to cultivate a positive and collegial workplace relationships - demonstrating integrity and ethics at all times.This job will start as hybrid with the potential of full remote.
The University of Pittsburgh is committed to championing all aspects of diversity, equity, inclusion, and accessibility within our community. This commitment is a fundamental value of the University and is crucial in helping us advance our mission, which includes attracting and retaining diverse workforces. We will continue to create and maintain an environment that allows individuals to discover, belong, contribute, and grow, while honoring the experiences, perspectives, and unique identities of all.
The University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity and diversity. EOE, including disability/vets.
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Assignment Category: Full-time regular
Job Classification: Staff.Medical Data Scientist I
Job Family: Research
Job Sub Family: Data Science
Campus: Pittsburgh
Minimum Education Level Required: Master's Degree
Will this position accept substitution in lieu of education or experience: Combination of education and relevant experience will be considered in lieu of education and/ or experience requirement.
Work Schedule: M-F 8-4
Work Arrangement: Hybrid: Combination of On-Campus and Remote work as determined by the department.
Hiring Range: TBD Based Upon Qualifications
Relocation_Offered: No
Visa Sponsorship Provided: No
Background Check: For position finalists, employment with the University will require successful completion of a background check
Child Protection Clearances: Not Applicable
Required Documents: Resume, Cover Letter
Optional Documents: Not Applicable
Essential Functions: • Assist in protocol development by implementing proper study design methodology, performing sample size and power calculations, and generating randomization schedules. • Make recommendations for appropriate statistical analyses and design to investigators and study team. • Collaborate on grants, presentations and manuscripts submitted for publication, including writing methods sections and analysis plans for incorporation into protocol and grant submissions. • Contribute to teaching biostatistical methodology to medical students, residents, and fellows. • Stay informed of statistical techniques as applied to musculoskeletal research issues by reading journals and/or attending courses/programming meetings.
