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Johns Hopkins University

Data Scientist (Research Associate, Non-Tenure Track Faculty)

Johns Hopkins University, Baltimore, Maryland, United States, 21276


Requisition #:

A-138543-11Status:

Full TimeType:

FacultySchool:

School of MedicineDepartment/Program:

Quantitative SciencesThe Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University fosters team science efforts, providing an environment where statisticians can advance standard statistical pipelines and cutting-edge quantitative science methodologies for state-of-art clinical studies. Thus, the members of the Division of Quantitative Sciences have strong collaborations with Cancer Center investigators and quantitative science Departments in the broader Johns Hopkins University, including the Departments of Biostatistics and Epidemiology in the Bloomberg School of Public Health. This collaborative, transdisciplinary research and educational environment promoted by the Cancer Center and the broader Johns Hopkins University fosters a diverse and inclusive community, featuring strong mentorship and a career-path for faculty statisticians.The Data Scientist collaborates independently with principal investigators in statistical design and analysis of clinical and laboratory studies. Supervises and coordinates the work of staff statisticians, ensuring the appropriate and best use of standard and non-standard statistical methodologies for the design of studies and statistical analysis. Functions largely independently or as co-investigator to solve problems posed by clinical and laboratory investigators (including meetings, experimental design, analysis, and interim and final reports), and works with the Director of Oncology Quantitative Sciences Division and the Biostatistics Shared Resource Director of the Cancer Center to introduce and integrate novel analysis methods into the work of the statistical team as needed.Specific Duties/Responsibilities:

Serve as the Lead Biostatistician in projects with standard designsParticipate in team science projects serving as statistician in the Biostatistics Core of SPOREs, P01s and U54sDelegate duties to Biostatisticians working on the projects, providing coordination, oversight, direction and guidance as necessaryMonitor and coordinate the team's effort to meet project timelines and to ensure quality standards are metConsult independently with clinical and laboratory investigators to determine their needs with respect to the statistical design of studies and propose appropriate designs and analysis methodsCollaborate with investigators in the preparation of presentations and publications, making significant contributions to publicationsDetermine, research, and implement appropriate methodologic procedures for analysis of complex dataDetermine study design, perform sample size and power calculations, generate randomization schema, and write statistical sections for research protocols and manuscriptsConduct statistical analysis and interpret the results. Prepare interim and final reports of studies. Discuss with colleagues, investigators, and supervisor the need for any additional analyses and/or special methodologic requirementsManage computational workflows/pipelines to complete statistical or applied quantitative projects in an efficient and timely mannerParticipate on the Protocol Review CommitteeSupervision of Others:

Lead and supervise 1 - 2 junior Biostatisticians.Qualifications

Minimum Qualifications:Education:- Required: Doctoral degree in biostatistics, statistics, mathematics, or related fieldExperience:- Recent graduates with a PhD degree are welcome to apply- Experienced in cancer clinical trials and/or other cancer-related studies including study design and data analysis preferredSpecial Knowledge, Skills, and Abilities:- Excellent leadership and project management skills- Basic coaching and mentoring skills- Solid knowledge and expertise in statistics and its applications in laboratory, and clinical and translational research, demonstrated by publications- Experience with implementation of novel methods and/or innovation strategies- Organization and management skills: Ability to work independently and as part of a team; demonstrated time management skills; ability to multitask and assign priorities; demonstrated ability to manage highly detailed projects; ability to provide continuous quality and service improvement- Expert knowledge of procedural-oriented statistical languages, such as SAS, and/or R. In addition, a knowledge of other programming languages, such as Python is helpful- Excellent interpersonal skills in consulting with researchers and understanding their problems- Excellent writing and verbal skills in the preparation and presentation of reports. Attention to details is requiredThe Johns Hopkins University is committed to equal opportunity for its faculty, staff, and students. To that end, the university does not discriminate on the basis of sex, gender, marital status, pregnancy, race, color, ethnicity, national origin, age, disability, religion, sexual orientation, gender identity or expression, veteran status or other legally protected characteristic. The university is committed to providing qualified individuals access to all academic and employment programs, benefits and activities on the basis of demonstrated ability, performance and merit without regard to personal factors that are irrelevant to the program involved.Pre-Employment Information:The successful candidate(s) for this position will be subject to a pre-employment background check.

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