• Biostatistician

    Posted Date 10 months ago(12/1/2017 3:22 PM)
    Job ID
    2017-2708
    # of Openings
    1
    Job Location(s)
    US-MD-Bethesda
    Category
    Science
  • Overview

    Medical Science & Computing (MSC) is an exciting growth oriented company, dedicated to providing mission critical scientific and technical services to the Federal Government. We have a distinguished history of supporting the National Institutes of Health (NIH) and other government agencies. MSC offers a dynamic and upbeat work environment, excellent benefits and career growth opportunities.

     

    We attract the best people in the business with our competitive benefits package that includes medical, dental and vision coverage, 401k plan with employer contribution, paid holidays, vacation, Medical and Flexible Spending Accounts, Pre-Tax Transit Assistance and tuition reimbursement. If you enjoy being a part of a high performing, professional service and technology focused organization, please apply today!

    Duties & Responsibilities

    We are currently searching for a Biostatistician to provide support to the National Institutes of Health (NIH). The Lister Hill National Center for Biomedical Communications (LHC) which is part of the National Institutes of Health (NIH), requires the services of a biostatistician with experience in analyzing large, de-identified, medical record and clinical databases in who will be responsible for supporting the development of statistical methods for research projects. The ideal applicant will collaborate with LHC scientists (including physicians, engineers and computer scientists) in the design of formal studies and will participate in development of statistical methods to find important predictors of outcomes in large claim-based clinical database using various regression and survival models.This opportunity is a permanent, full-time position with MSC and it is on-site in Bethesda, Maryland.

     

    Key Responsibilities

    Manipulating CMS Medicare claims data using SAS. The task involves merging and consolidating different claim-level files and creating patient-level summary data. Analyzing patient-level study data to find important predictors for outcomes of interest. Experience in implementing propensity score approaches (matching, stratification and weighting) and in time to event data analysis is desirable to demonstrate experience in analyzing observational data. 

     

    Required Skills and Experience

    • M.S. degree in statistics or biostatistics with strong academic training in methodology.
    • Demonstrable expertise with implementing electronic health records, especially CMS Medicare claims data.
    •  Familiar with statistical models such as generalized linear models, survival analyses (Cox proportional hazard regression, Accelerated Failure time model, Fine-Gray sub-distribution hazard regression etc.), and Mixed model. High degree of programming proficiency in SAS/R/Stata
    • Expertise in SAS. Example: SAS/SQL, SAS/STAT such as PHREG, LIFEREG, GENMOD, GLIMMIX etc.
    • Experience in R programming language and Stata plus.
    • Good working knowledge of SAS and time efficient programing is a plus.
    • Good understanding in Medicare/Medicaid
    • Experience with analysis of clinical and medical record data

    Requirements

    • Write clean, consistent and well-documented code
    • Excellent oral, and written communication skills, and ability to document projects and provide status reports.
    • Excellent team and interpersonal skills. Ability to both take direction and work in a self-directed environment, effectively interact with all levels of staff and external contacts, and ability to work as an effective team member.
    • Excellent organization and time management skills, and flexibility to handle a variety of tasks, and shift priorities as needed. 

    Medical Science & Computing 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, or protected Veteran status.

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