Clinical Information Science Intern

AstraZenecaGaithersburg, MD
8d$37 - $39Onsite

About The Position

We are looking for Sophomore and Junior students majoring in Computer Science, Information Sciences, Engineering, Data science for a 12-week internship role at our site in Gaithersburg, MD from May 18 2026 to August 7 2026. Position Description: Data sourcing and preparation: Identify, ingest, and clean structured and unstructured datasets; document data lineage, assumptions, and quality checks. Reproducible workflows: Use Git, notebooks, and code review to ensure version control, documentation, and repeatable analyses. Stakeholder collaboration: Gather requirements, validate use cases, and iterate on findings with internal and external partners.

Requirements

  • Sophomore and Junior students majoring in Computer Science, Information Sciences, Engineering, Data science, or a related field.
  • Candidates must have an expected graduation date after August 2026.
  • Programming proficiency in at least one programming language (for e.g. Python, R, SQL): Data manipulation, analysis, and basic modeling using clean, well-documented code.
  • ETL understanding: Extract, transform, and load data from multiple sources into analytics-ready structures and storage.
  • Basic level of Database knowledge: Work with relational databases and write efficient SQL for data retrieval, joins, and performance-aware queries
  • Enthusiasm for collaboration, cross-functional projects, public speaking, and presentation design.
  • US Work Authorization is required at time of application.
  • Ability to report onsite to Gaithersburg, MD site 3 days per week.

Nice To Haves

  • Data visualization experience preferable (Tableau, Power BI, similar): Build intuitive dashboards and charts tailored to stakeholder needs.
  • Machine Learning and AI Familiarity preferred

Responsibilities

  • Data sourcing and preparation: Identify, ingest, and clean structured and unstructured datasets; document data lineage, assumptions, and quality checks.
  • Reproducible workflows: Use Git, notebooks, and code review to ensure version control, documentation, and repeatable analyses.
  • Stakeholder collaboration: Gather requirements, validate use cases, and iterate on findings with internal and external partners.
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