Programmer Analyst I

University of Southern California
Los Angeles, United States of America
2 days ago

Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Junior
Compensation
$ 97K

Job location

Los Angeles, United States of America

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Data analysis
Big Data
Bioinformatics
Cloud Computing
Computer Programming
Data Visualization
Relational Databases
Database Development
Python
PostgreSQL
Scientific Computating
Software Engineering
Data Processing
GIT
Semi-structured Data
Information Technology
Data Management
Software Version Control
Programming Languages

Job description

The USC Center for Translational Exposomics is seeking a Programming Analyst I to support the development and implementation of data systems and analytical pipelines for environmental and multi-omics research., The Programming Analyst I will contribute to the design, development, and maintenance of data infrastructure and analytical tools supporting large-scale environmental and omics datasets., * Develop, implement, and maintain data processing pipelines for environmental exposure, metabolomics, and other high-dimensional datasets

  • Support integration and harmonization of multi-source data, including cohort, clinical, and laboratory-based datasets
  • Collaborate with investigators and research staff to translate scientific questions into reproducible computational workflows
  • Optimize data workflows for performance, scalability, and reproducibility across projects
  • Write, test, and maintain clean, well-documented code following best practices in scientific computing
  • Assist in database development and management, including structured and semi-structured data systems
  • Contribute to data quality control, validation, and standardization efforts across studies
  • Support visualization and reporting of analytical results for scientific publications and presentations
  • Participate in collaborative team environments, communicating progress, challenges, and solutions effectively

Requirements

  • Bachelor's degree in computer science, data science, bioinformatics, public health or a related field
  • Preferred of 1-2 years of experience in programming, data analysis, or scientific computing
  • Proficiency in at least one programming language (e.g., Python, R)
  • Experience working with large, complex datasets
  • Familiarity with data processing, cleaning, and transformation workflows
  • Experience with relational databases (e.g., PostgreSQL) and/or data management systems
  • Understanding of version control (e.g., Git) and reproducible research practices
  • Ability to work collaboratively in interdisciplinary research teams
  • Preferred Qualifications
  • Experience working with environmental health, epidemiologic, or omics datasets (e.g., metabolomics, genomics)
  • Familiarity with statistical or bioinformatics workflows
  • Experience with high-performance or cloud computing environments (e.g., AWS)
  • Experience with data visualization tools and scientific reporting

The hourly rate pay range for this position is $36.55 - $46.67. When extending an offer of employment, the University of Southern California considers factors such as the scope and responsibilities of the position, the candidate's work experience, education/training, key skills, internal peer equity, grant funding, and external market conditions. Minimum Education: Bachelor's degree, Combined work experience and education as equivalent Minimum Experience: 0 - 6 months Minimum Field of Expertise: General knowledge of programming and documentation procedures and programming methods and operator instructions. Knowledge of one or more appropriate computer languages.

About the company

The University of Southern California (USC) Center for Translational Exposomics (CTER) is a leading interdisciplinary research center focused on understanding how environmental exposures impact human health across the lifespan. The Center integrates environmental science, epidemiology, multi-omics technologies, and data science to advance discovery and translation in environmental health. CTER's collaborative environment brings together researchers from medicine, engineering, public health, and data science to analyze complex, high-dimensional datasets, including environmental exposure measurements, metabolomics, genomics, and clinical data. The Center is committed to developing scalable, data-driven approaches that translate scientific discoveries into actionable public health and policy solutions.

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