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    Data Analyst at - Nairobi, Kenya - Ruaraka Uhai Neema Hospital

    Ruaraka Uhai Neema Hospital
    Ruaraka Uhai Neema Hospital Nairobi, Kenya

    1 week ago

    Default job background
    Full time
    Description

    Ruaraka Uhai Neema Hospital (RUNH) is proving every single day that it is possible to deliver healthcare to all with quality and commitment.

    RUNH was founded by World Friends in partnership with the Catholic Archdiocese of Nairobi and CISP and has been offering quality healthcare at affordable prices to our Nairobi communities since 2009.

    Summary


    The Data Analyst will be responsible for conducting full lifecycle analysis, monitoring performance and quality control plans to identify improvements.

    Duties and Responsibilities for the Data Analyst Job

    Interpreting data, analyzing results using statistical techniques and providing ongoing reports;
    Developing and implementing databases, data collection systems, data analytics and other strategies that optimize statistical efficiency and quality;
    Acquiring data from primary or secondary data sources and maintaining databases/data systems;
    Identifying, analyzing and interpreting trends or patterns in complex data sets;
    Filtering and "cleaning" data by reviewing computer reports, printouts, and performance indicators to locate and correct code problems;

    Identifying gaps and scopes for enhancement of the hospital HMIS, thus recommending improvements to better serve quality data purposes and reporting requirements.

    Data Analyst Job Qualifications

    Bachelor of Science in Mathematics, Economics, Computer Science, Statistics or its accepted equivalent;
    Proven working experience of at least one (1) year as a data analyst;
    Previous experience in a healthcare provider setting is considered an advantage;
    Proven knowledge and experience in data models, database design development, data mining and segmentation techniques;
    Proven Knowledge and experience in using statistical packages for analyzing datasets (Excel, SPSS, SAS, etc.)

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