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Data Scientist and Application Programmer

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POST DATE 9/2/2016
END DATE 2/19/2017

University of California - Los Angeles Medical Centers Los Angeles, CA

Los Angeles, CA
AJE Ref #
Job Classification
Full Time
Job Type
Company Ref #
Mid-Career (2 - 15 years)
Bachelors Degree


Job Title:
Data Scientist and Application Programmer

UCLA Title:
Programmer/Analyst III

Job No.:

Work Hours:

Work Location:
924 Westwood Blvd. Suite 420

Job Type:


Minimum Salary:
$28.38 / $4938

Maximum Salary:
$56.03 / $9750

Layoff Referral Deadline:

Bargaining Unit:


The incumbent will serve as a data scientist and application programmer in the service of the UCLA Department of Radiological Sciences. Projects will include developing methodologies and algorithms for analyzing and visualizing large, complicated clinical data sets. In addtion, the incumbant will also work on designing, implementing, testing, and maintaining clinical web-based applications and databases. The incumbant will have the opportunity to work with faculty researchers, clinicians, and IT staff to translate innovations in natural language processing, medical image processing, and machine learning into cutting-edge biomedical applications. The incumbent is expected to work in accordance with all institutional and regulatory policies governing confidentiality of protected health information in clinical and research practice. Incumbent will report to faculty members. Incumbent is expected to meet deadlines established by faculty members and all involved developers. Incumbent is expected to perform duties largely independently. Think creatively to apply current research tools, or design new tools, for the analysis of large, complex clinical datasets. Lead programming of web-based applications using Java, RESTful services, HTML, SQL, CSS, JSON, SSL, XML, and JavaScript to combine and visualize clinical data from disparate sources. Design and implement backend code and SQL databases for clinical and research projects including schema design, security, administration, backup procedures, and ETL procedures from source data repository. Must work independently, but interact well with others in a team environment, including liaising with counterparts. Must devote significant efforts to unit testing, bug fixing, and satisfying user requirements. Must be able to adapt and work efficiently under evolving technological demands as projects proceed.


Technical expertise in a programming language such as Java, Python, or C++. Technical expertise in web development frameworks and technologies such as Grails, Django, Node.js, JSON, REST, JSP, Javascript, HTML, CSS, XML, AJAX. Experience in configuring and working in Apache web application environments. Knowledge and experience in the development of entity-relationship databases, with technical expertise in SQL. Ability to comply with regulatory policies surrounding protected health information. Must have the ability to ensure projects meet all business requirements and conform to development standards and guidelines. Excellent oral and written communication skills, including demonstrated ability to write clear, concise and comprehensive system documentation and office correspondence. Working knowledge of applications such as MS Word, Excel, PowerPoint, Access, and e-mail, communications protocols and communication software. Interpersonal skills to work effectively with staff, faculty and other administrators in the UCLA information technology arena. Self-direction to tackle new problems and overcome barriers within the scope of departmental research projects. BS in Computer Science, Electrical Engineering, Information Science, or related field. Two years of relevant professional experience or MS in Computer Science, Biomedical Informatics, Electrical Engineering, Information Science, or related field. PhD in Computer Science, Electrical Engineering, Information Science, Biomedical informatics, or related field.Experience with machine learning fundamentals and analysis tools (e.g., Matlab, SciPy, NumPy, RapidMiner, Torch, etc.). Basic knowledge of statistical analysis methodologies and tools (e.g., Stata, SAS, etc.). Knowledge and experience in information extraction from unstructured free-text data. Knowledge and experience in data standardization and cleaning techniques (e.g., coding methods, de-identification of sensitive data, etc.). Familiarity with clinical data models and standards (e.g., HL7, DICOM, Epic Clarity, etc.)

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