RWE SAS Programmer Intern for Biostatistics & Data Prep

Be The Match in

Minneapolis (MN)

On-site

USD 30,000 - 47,000

Full time

14 days+

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Job summary

Be The Match is seeking a Biostatistics Intern - SAS Programmer (Finance) to support real-world evidence research within the Biostatistics team. The role focuses on data programming using SAS to prepare, transform, and quality-check datasets for observational studies and registry analyses.

You will collaborate with biostatisticians, data operations, and clinical teams to ensure clean, standardized, and analysis-ready data.

Qualifications

  • Must be enrolled in the second year of a Master's degree program in Biostatistics, Statistics, Public Health, Data Science, or have graduated within the past 6 months.
  • 1+ years of hands-on programming through research, internships, projects, or related work.
  • Strong knowledge of Base SAS, PROC SQL, and data step programming.
  • Familiarity with SAS macros.
  • Availability to work 20-29 hours per week during standard business hours.
  • Internship duration 9-12 months; anticipated start late August through mid-September 2026.

Responsibilities

  • Support development of programming specifications defining variable derivations and data standards.
  • Perform data cleaning, transformation, and preparation of large clinical registry datasets using SAS.
  • Develop and maintain SAS programs and macros to support reproducible workflows.
  • Translate specifications into SAS code to prepare analysis-ready datasets and implement derivation logic.
  • Merge multiple data sources with QA assessments to ensure proper merging.
  • Generate summary outputs such as tables, listings and frequency reports.

Skills

Base SAS
Data step programming
SAS macros
PROC SQL

Education

Master's degree in Biostatistics

Tools

SAS
SQL

Job description

Be The Match is seeking a Biostatistics Intern - SAS Programmer (Finance) to support real-world evidence research within the Biostatistics team. The role focuses on data programming using SAS to prepare, transform, and quality-check datasets for observational studies and registry analyses.

You will collaborate with biostatisticians, data operations, and clinical teams to ensure clean, standardized, and analysis-ready data.

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