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Biostatistician - Hybrid - 133084

Job Description

UCSD Layoff from Career Appointment: Apply by 11/12/2024 for consideration with preference for rehire. All layoff applicants should contact their Employment Advisor.

Special Selection Applicants: Apply by 11/20/2024. Eligible Special Selection clients should contact their Disability Counselor for assistance.

This position will work a hybrid schedule which includes a combination of working both onsite at Moores Cancer Center and remote.

DESCRIPTION

The Moores Cancer Center (MCC) is one of just 57 NCI-designated Comprehensive Cancer Centers in the United States and the only one in San Diego County. As a consortium cancer center, it is a collaborative partnership between the UCSD: encompassing 28 departments, 6 schools (School of Medicine, Skaggs School of Pharmacy and Pharmaceutical Sciences, School of Public Health, Jacobs School of Engineering, School of Biological Sciences & the School of Physical Sciences), UCSD Health oncology hospitals and clinics; the basic and public health research and outreach of San Diego State University (SDSU), and the basic and translational research of the La Jolla Institute of Immunology (LJI). These various programs and units are all dedicated to fulfilling the Moores Cancer Center's mission of reducing cancer's burden. As such, it ranks among the top centers in the nation conducting the continuum of cancer research, providing advanced patient care, and serving the community through outreach and education programs. As a top-ranking, future-oriented organization, we offer challenging career opportunities in a fast-paced and innovative environment. Moores Cancer Center follows a progressive philosophy of career-path development for its employees including opportunities for cross-training, professional development, and progressive responsibility.

MCC's mission is to transform cancer care in our catchment area and beyond by driving exceptional scientific discoveries and innovations in prevention, detection, care, and training. MCC will make a global impact on improving health by reducing cancer burden through accelerated discovery and translation, compassionate and interdisciplinary care, education and community engagement, with the foundation of our core values - Excellence, Innovation and Risk-Taking, Collaboration, Diversity and Service.

Under the direction of the Principal Investigator, this position will provide statistical, bioinformatics, data management and report support. This position will involve collaboration with a diverse team of clinicians, statisticians, and epidemiologists focused on advancing research in cancer detection and prevention using the Department of Veterans Affairs (VA) Informatics and Computing Infrastructure (VINCI) and other data infrastructures. Responsible for participation in meeting with medical and scientific researchers to discuss statistical issues of study design, data analysis, and protocol, grant, and manuscript preparation; develop longer term collaboration with researchers, including understanding of scientific context. Assist researchers in calculating power and sample sizes, developing appropriate hypotheses and data analysis plans, in carrying out appropriate statistical analyses, and in preparing written interpretation of statistical methods and results. Provide modification and extension of existing statistical methodology and develop new methodology as appropriate. Use independent identification and application of appropriate statistical approaches, utilizing both conventional and state-of-arts methods, and assist with developing new methodology. Perform data queries and data analysis using SQL, SAS and/or R. Generate research data reports and select methods and techniques for statistical analysis solutions.

Provide support for manuscript writing and submission, including addressing and drafting the response to the reviewer's comments for limited studies. Independently work on developing an innovative electronic phenotyping algorithm for large electronic health data abstraction, as well as work on data preparation for large scale data analysis.

MINIMUM QUALIFICATIONS
  • Six years of related experience, education/training, OR a Bachelor's degree in related area plus two years of related experience/training.

  • Theoretical knowledge of statistics, applied mathematics, or related field. Ability to read and understand the applied statistics literature. Experience to adapt existing methodology to new situations. Experience providing written interpretation of statistical methods and results, in a manner suitable for publication.

  • Demonstrated experience with data analysis, computer programming and graphing complex and custom statistical programming using statistical software, including R and SAS.

  • Demonstrated working experience with statistical methods and models incorporating a broad range of study designs and traditional and modern statistical approaches such as linear, logistic, Poisson, survival and longitudinal models, multiple testing adjustment methods, and machine learning techniques.

  • Working knowledge of research function. Demonstrated experience in biostatistics/bioinformatics and biomedical data analysis and management.

  • Working skills in statistical analysis, systems programming, database design and data security measures.

  • Working skills in analysis and consultation. Proven experience with analytic, inductive and deductive reasoning skills.

  • Demonstrated experience and expertise with database queries, management, and quality assurance using SQL.

  • Skills to communicate complex information in a clear and concise manner both verbally and in writing. Proven skill to communicate methods and results to provide interpretive information to scientific Investigators from which researchers can draw conclusions.

  • Strong interpersonal and organizational skills. Ability to communicate with physicians, investigators and colleagues. Ability to communicate effectively in both verbal and written form.

  • Excellent time management and organizational skills. Demonstrated skill in prioritizing multiple responsibilities and tasks. Ability to work in busy team-oriented environment and meet deadlines.

  • Demonstrated knowledge of Word, Excel, PowerPoint, and relational database concepts.

PREFERRED QUALIFICATIONS
  • Experience with REDCap.

  • Demonstrated working experience with VINCI workspace, VA VistA, and/or the National Patient Care Database. Training and experience with using large scale VA healthcare data for research.

  • Familiarity with colorectal cancer terminology. Familiarity with methods applicable to clinical, epidemiological investigation. Demonstrated experience conducting quantitative research.

  • Experience with integrating VA healthcare data with Centers for Medicare and Medicaid Services administrative claims data.

  • Experience with complex cohort studies, and/or experience in conduct of meta-analyses

SPECIAL CONDITIONS
  • Employment is subject to a criminal background check.

Pay Transparency Act

Annual Full Pay Range: $69,500 - $123,500 (will be prorated if the appointment percentage is less than 100%)

Hourly Equivalent: $33.29 - $59.15

Factors in determining the appropriate compensation for a role include experience, skills, knowledge, abilities, education, licensure and certifications, and other business and organizational needs. The Hiring Pay Scale referenced in the job posting is the budgeted salary or hourly range that the University reasonably expects to pay for this position. The Annual Full Pay Range may be broader than what the University anticipates to pay for this position, based on internal equity, budget, and collective bargaining agreements (when applicable).


UC San Diego Health is an Equal Opportunity/Affirmative Action Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, age, protected veteran status, gender identity or sexual orientation. For the complete University of California nondiscrimination and affirmative action policy see: http://www-hr.ucsd.edu/saa/nondiscr.html

 

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