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This position is for a data scientist/statistical analyst in the Center for Craniofacial and Dental Genetics (CCDG), an interdisciplinary research group focused on understanding the genetic basis of complex oral, dental, and facial conditions. The analyst will be responsible for carrying out analyses of various imaging based and animal model datasets. Common tasks include accessing and obtaining datasets from controlled access data repositories, performing data cleaning and quality control steps, and conducting analyses of imaging datasets including various available pipelines. This analyst will also have the chance to work on sequence-based data such as RNAseq and MethylSeq.
The analyst will also be required to summarize their findings for CCDG investigators in the form of presentations and publications. This position will involve frequent interaction with faculty investigators, data management specialists, and statistical analysts in the CCDG as well as external collaborators. Prior experience with imaging data analysis, managing large datasets, and proficiency with one or more programing languages is required (R, Matlab, VTK, Python, SQL, etc.). Additional programming capabilities and familiarity with image analysis is desirable. The candidate must be highly organized, detail oriented, and possess excellent verbal and written communication abilities. The candidate will be expected to be able to complete tasks with minimal supervision, achieving greater independence over time.
Job SummaryAssists in the execution of research objectives, data collection, and data management. Performs routine procedures, statistical analysis, scientific analysis, and reporting. Integrates data and data sets, performs descriptive and exploratory analysis, and creates routine reports and analysis reporting tools. Utilizes statistical software and adheres to all protocols.
Essential FunctionsAssists in the execution of research objectives, data collection, and data management. Performs routine procedures, statistical analysis, scientific analysis, and reporting. Collects, organizes, maintains, reviews, and integrates data and data sets to support analysis and study design. Performs descriptive and exploratory analyses. Creates routine reports, charts, exhibits, and other relevant data summarizations and analysis reporting tools. Utilizes statistical software in analysis and interpretation of research data. Adheres to research protocols; ensures compliance with all regulations.
Physical EffortMust be able to sit or stand for prolonged periods of time.
The University of Pittsburgh is committed to championing all aspects of diversity, equity, inclusion, and accessibility within our community. This commitment is a fundamental value of the University and is crucial in helping us advance our mission, which includes attracting and retaining diverse workforces. We will continue to create and maintain an environment that allows individuals to discover, belong, contribute, and grow, while honoring the experiences, perspectives, and unique identities of all.
The University of Pittsburgh is an Affirmative Action/Equal Opportunity Employer and values equality of opportunity, human dignity and diversity. EOE, including disability/vets.
Assignment Category: Full-time regularPI238110173
Full Time
Consumer Services
$75k-91k (estimate)
02/09/2024
04/15/2024
pitt.edu
MANVILLE, RI
15,000 - 50,000
1787
Private
TONY BORGES
$1B - $3B
Consumer Services
University of Pittsburgh is an educational institution that offers undergraduate and postgraduate degree programs for students.
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Data scientists work closely with business stakeholders to understand their goals and determine how data can be used to achieve those goals.
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Data scientists are meant to use their technology and social science skills to develop different trends and manage data wisely.
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Data scientist will need to meet with their business stakeholders early and often to ensure that they are on the same page about the goals and deliverables of the project.
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Data scientists may spend some of their time working on ad hoc data requests, but these types of requests should only take up a small portion of their time.
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Analyzing data from multiple angles and searching for trends that could reveal problems or opportunities.
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Data scientists lay a solid foundation to help perform all kinds of analysis.
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Data scientists are also expected to have stronger software engineering skills that data analysts.
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Business analysts are focused on reporting, just like data analysts.
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A data scientist should understand the assumptions that need to be met for each statistical test.
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