Data Scientist at University of Chicago | Chicago, IL, US | Rezi

Data Scientist at University of Chicago

Data Scientist

University of Chicago · Chicago, IL, US

1 months ago

Data Scientist

University of Chicago · Chicago, IL, US

a month ago
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About the Role

The Data Scientist will lead data science research efforts within the breast cancer program in the Section of Hematology/Oncology.

Responsibilities

  • Manage the program’s projects.
  • Develop frameworks for housing multi-modal clinical data – including genomic, pathology, and radiographic imaging data.
  • Develop and code data dictionaries for discrete data.
  • Write, implement, and develop efficient code and machine learning tools and pipelines for data processing and analysis.
  • Work with collaborators to implement emerging external computational tools for program data.
  • Draft grant proposals.
  • Develop training material.
  • Keep lab's knowledge-based trainings up to date.
  • Supervise trainees.
  • Perform reproducible genomic data analysis.
  • Calibrate data between large and complex research and administrative datasets.
  • Guide and may set the operational protocols for collecting and analyzing information from the University's various internal data systems as well as from external sources.
  • Design and evaluate statistical models and reproducible data processing pipelines using expertise of best practices in machine learning and statistical inference.
  • Provide expertise for high level or complex data-related requests and engage other IT resources as needed.
  • Analyze moderately complex data sets for the purpose of extracting and purposefully using applicable information.
  • Provide 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.
  • Perform other related work as needed.

Requirements

  • College or university degree in a related field.
  • 2-5 years of work experience in a related job discipline.
  • Proficiency in Linux/Ubuntu OS including basic file and user management, ssh.
  • Familiarity with tmux, SLURM.
  • Experience in python including torch and scikit-learn libraries strongly preferred.
  • Experience in working with image data or unstructured text data with large language models.

Skills

  • Strong Analytical skills.
  • Problem-solving skills.
  • Organizational skills.
  • Verbal and written communication skills.
  • Ability to work independently and as part of a team.

Location

  • Chicago, IL

Work Type

  • Full-time

Experience Level

  • 2-5 years

Education Level

  • College or university degree in related field
  • Advanced degree in computer science

Salary/Compensations

  • $70,000.00 - $100,000.00

Benefits

  • Health, retirement, and paid time off.

About the Company

  • 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.

Equal Opportunity

  • 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.
  • 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.