Chicago, IL, USA
81 days ago
Data Analyst

Department
 

BSD MED - Hematology and Oncology - Garassino Research Staff


About the Department
 

The Section of Hematology/Oncology has a proud and long tradition of excellence in research-based patient care and clinical discovery. Ranked among the finest cancer programs in the country, the Section is comprised of nationally and internationally known faculty with expertise in all major types of malignancies, blood disorders, and experimental therapies.


Job Summary
 

Dr. Garassino’s group is seeking a Data Analyst to support data management across research projects. This position will play a supporting role in the collection, organization, and analysis of data sourced from diverse internal and external sources. Working closely with senior team members, this hire will contribute to data analysis assignments essential for supporting research projects. Responsibilities include ensuring data accuracy, validity, and quality assurance across different systems, as well as generating reports and insights crucial for informed decision-making. The analyst is expected to focus their efforts on projects that include – but are not limited to – digital pathology data.

This position will collaborate with study team members across the Center to accurately address data needs as they arise and will actively familiarize themselves with the history and complexity of longitudinal datasets across multiple established research projects.

An ideal candidate will have a working knowledge of the Research Electronic Data Capture (REDCap) system, knowledge of research methodologies and data analysis, experience with coding languages such as R and Python, and a demonstrated commitment to communication and collaboration.

Responsibilities

Develops and enhances climate and impact research tools.

Manages and optimizes petabyte-scale data storage systems.

Collaborates with researchers for new analyses with large datasets.

Trains research assistants in the use of new and existing computational tools and provides support.

Oversees code management and organization within the lab.

Ensures efficient data storage accessibility and integrity.

Contributes insights to research and produces output for policymakers.

Develops, maintains, and extends computational tools and data storage systems for climate and impact research.

Supports researchers in conducting new analyses by working with petabyte-scale in multiple computing environments.

Acts as a point of contact for code management and data storage at the Lab.

Supports data collection and analytical needs of research projects. Conducts literature reviews and helps write reports and manuscripts. Ensures project compliance with different policies, procedures, directives, and mandates.

Takes responsibility for the following non-laboratory duties: transcribing and coding data; developing data collection instruments; presenting research; and recruiting and scheduling research subjects. Acquires higher-level skills and knowledge in the process.

Analyzes moderately complex data sets for the purpose of extracting and purposefully using applicable information.

Provides professional support to staff or faculty members in defining the project and applying principals of data science in manipulation, statistical applications, programming, analysis and modeling.

Performs other related work as needed.


Minimum Qualifications
 

Education:

Minimum requirements include a college or university degree in related field.

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Work Experience:

Minimum requirements include knowledge and skills developed through 2-5 years of work experience in a related job discipline.

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Certifications:

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Preferred Qualifications


Education:

Advanced degree in a related field.

Experience:

Experience training team members with software tools.

Strong background in Python; data analysis tools (pandas, xarray), climate data storage formats (e.g. NetCDF, Zarr).

Familiarity with version control (git).

Experience with geospatial and temporal data visualization.

Strong background in distributed computing tools (dask).

High-performance computing clusters.

Linux command line/bash scripting.

Familiarity with R and/or STATA.

Preferred Competencies

Strong communication skills.

Strong multi-disciplinary collaboration skills.

Application Documents

Resume (required)

Cover Letter (required)


When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application.


Job Family
 

Research


Role Impact
 

Individual Contributor


FLSA Status
 

Exempt


Pay Frequency
 

Monthly


Scheduled Weekly Hours
 

40


Benefits Eligible
 

Yes


Drug Test Required
 

No


Health Screen Required
 

No


Motor Vehicle Record Inquiry Required
 

No


Posting Statement
 

The University of Chicago is an Affirmative Action/Equal Opportunity/Disabled/Veterans and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, national or ethnic origin, age, status as an individual with a disability, military or veteran status, genetic information, or other protected classes under the law. For additional information please see the University's Notice of Nondiscrimination.

 

Staff Job seekers in need of a reasonable accommodation to complete the application process should call 773-702-5800 or submit a request via Applicant Inquiry Form.

 

We seek a diverse pool of applicants who wish to join an academic community that places the highest value on rigorous inquiry and encourages a diversity of perspectives, experiences, groups of individuals, and ideas to inform and stimulate intellectual challenge, engagement, and exchange.

 

All offers of employment are contingent upon a background check that includes a review of conviction history.  A conviction does not automatically preclude University employment.  Rather, the University considers conviction information on a case-by-case basis and assesses the nature of the offense, the circumstances surrounding it, the proximity in time of the conviction, and its relevance to the position.

 

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