Data Analyst

The Department of Biomedical Informatics ( DBMI ) is currently seeking a Data Analyst (DA) to work with biomedical scientists in applying advanced data analysis methods to biomedical data to discover causal relationships. In particular, the DA will learn and apply state-of-the-art causal discovery algorithms to large biomedical datasets to generate causal networks that provide scientific insight. The DA will participate on a data analysis team that consists of biomedical scientists throughout the University of Pittsburgh and faculty in DBMI . The biomedical scientists will represent a wide variety of departments and biomedical fields of study. The DBMI faculty will have extensive experience in the causal discovery algorithms being used. The DA will work with DBMI faculty and biomedical scientists to a.) prepare the data for analysis, b.) determine the appropriate analysis algorithms to apply to the data, c.) apply those algorithms to the data, d.) interpret the results of analyses, and e.) document the results for publication.

The data to be analyzed will include, but are not limited to, gene expression, micro RNA , SNP , methylation, Next Gen sequencing, proteomic measurements, and clinical data from electronic medical record systems. The DA will be a contact person for the data analysis requests and will participate in projects from start to finish while providing data analysis support.

Responsibilities will include but are not limited to the following:

• developing project plans
• allocating resources
• coordinating timelines
• monitoring and documenting progress for multiple projects
• causal analysis and interpretation of results
• selective software development
• assisting with publications and grant proposals
• evaluating and establishing the requirements and resources for projects (including hardware, software, and storage)
• communicating results to investigators in a timely manner

The DA must be creative and able to multitask, develop priorities, work in a fast-paced collaborative environment, adapt to changing needs, and work well independently and collaboratively, as they may work on multiple projects simultaneously.

Education Required

Baccalaureate

Minimum Related Experience Level Required

5-6 years experience

Additional Education and/or Experience Essential to the Position

Master’s Degree preferred; Bachelor’s accepted with five years of experience in computational data analysis and software development.

Five years of experience in software development and data mining and analysis. A solid understanding of modern biology, including knowledge of data of the following types: gene expression, micro RNA , SNP , methylation, Next Gen sequencing, proteomic measurements, and clinical data from electronic medical record systems. Fluency with basic probability and basic statistics. Strong background in bioinformatics, computer science, biology, or a related discipline. Incumbent must be fluent in Java and Python.

Required Licenses/Certifications

Child Protection Clearances

The following PA Act 153 clearances and background checks may be required prior to commencement of employment and as a condition of continued employment: PA State Police Criminal Record Check, FBI Criminal Record Check, PA Child Abuse History Clearance.

Background Check

For position finalists, employment with the University will require successful completion of a background check.

Assignment Category

Regular, Full-Time

Percent Effort

100

Scheduled Work Hours

8:00 a.m. – 4:30 p.m.

If Varied Work Schedule, Please Specify

If Part Time, Actual Standard Weekly Hours

Campus

Pittsburgh

University Benefits

The University offers an excellent comprehensive benefits package for all full-time and part-time regular employees including:

• Education benefits and a retirement plan with employer match
• Group medical insurance, life insurance, and optional vision and dental insurance
• Free transit service within Allegheny County for employees of the Oakland campus (Port Authority Transit)
• Time off benefits including vacation, sick and personal time