Data Science, Analyst Job at University of Chicago in Chicago

University of Chicago provided pay range This range is provided by University of Chicago. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range $24.04/yr - $31.25/yr Department BSD MED - Hematology and Oncology - Torcasso 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 The Data Science Analyst will work to maintain and deploy algorithms for accurate detection, segmentation, and classification of cells and structures in biomedical image data. Additionally, the candidate will analyze spatial transcriptomic data to evaluate spatial patterns of genes in tissues. They will primarily work on projects involving spatial characterization of cells and genes in the tumor microenvironment of breast and bladder cancers. The candidate should be proficient in Python with a familiarity of specific libraries/APIs including sci‑kit learn, pandas, skimage, and PyTorch. Strong interpersonal and communication skills are also required for successful integration into a team of researchers. Responsibilities Optimize and maintain algorithms in biomedical image analysis pipelines. Validate algorithm performance on novel datasets. Analyze spatial transcriptomic data. Perform statistical analyses on data extracted from bio‑images and other spatial data. Documentation and versioning of code and results. Assist in analyzing data for the purpose of extracting applicable information. Perform research projects that provide analysis for a number of programs and initiatives. May assist staff or faculty members with data manipulation, statistical applications, programming, analysis and modeling on a scheduled or ad‑hoc basis. Performs other related work as needed. Education: Minimum Qualifications Minimum requirements include a college or university degree in a related field. Work Experience Minimum requirements include knowledge and skills developed through Preferred Qualifications Advanced degree in Computer Science, Bioinformatics, or Data Science. Experience processing and managing both image and tabular data. Proficiency in Python, BASH, SLURM and PyTorch; familiarity with R. Analytical skills. Problem‑solving skills. Attention to detail. Organizational skills. Verbal and written communication skills. Ability to work independently and as a team. Application Documents Resume/CV (required) Cover Letter (preferred) When applying, the document(s) MUST be uploaded via the My Experience page, in the section titled Application Documents of the application. Seniority level Entry level Employment type Other Job function Information Technology Industries Higher Education Job Family Research Role Impact Individual Contributor Scheduled Weekly Hours 40 Drug Test Required No Health Screen Required No Motor Vehicle Record Inquiry Required No Pay Rate Type Hourly FLSA Status Non‑Exempt Pay Range $24.04 - $31.25 Benefits Eligible Yes Posting Statement The University of Chicago is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, sexual orientation, gender, gender identity, or expression, national or ethnic origin, shared ancestry, 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. 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. 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. #J-18808-Ljbffr