Senior R Statistical Programmer - Oncology (Remote)

Shree Narayani Networking Solutions Pvt Ltd; Delaware; Remote; USD 83,000 - 152,000; Full time

Job summary

Clinical statistical programmer with hands-on SDTM, ADaM, and TLF production and validation experience in R using pharmaverse packages, supporting an end-to-end R workflow alongside existing SAS code.

Responsibilities include building SDTM datasets from raw EDC data, validating ADaM in R, producing TLFs and submission-ready datasets, with QC of SAS and R outputs, and collaboration on SAPs and timelines.

Qualifications

• BS/MS in Statistics, Biostatistics, Mathematics, or related field.
• 5+ years of clinical statistical programming with CDISC SDTM and/or ADaM.
• 2+ years producing clinical outputs in R using pharmaverse, including admiral for ADaM and rtables/tern (or similar TLF packages like gtsummary or Tplyr).
• R outputs produced for actual study deliverables (CSR, DSMB, or interim analyses).
• Strong R programming skills, including tidyverse, RMarkdown/Quarto, and Git/GitHub.
• SAS experience, to work alongside existing SAS code.

Responsibilities

• Develop SDTM datasets from raw EDC data in R (sdtm.oak).
• Develop and validate ADaM datasets in R (admiral).
• Produce TLFs in R (rtables/tern) and submission-ready datasets (xportr) for clinical study reports and regulatory submissions.
• Perform independent QC/double programming of SAS and R outputs.
• Collaborate with biostatisticians and study teams on SAPs, specs, and timelines.

Skills

R programming

SAS

tidyverse

RMarkdown/Quarto

Git/GitHub

SDTM

ADaM

gtsummary

Tplyr

Education

BS in Statistics

MS in Biostatistics

Tools

sdtm.oak

admiral

rtables/tern

xportr

Job description

Clinical statistical programmer with hands-on SDTM, ADaM, and TLF production and validation experience in R using pharmaverse packages, supporting an end-to-end R workflow alongside existing SAS code.

Responsibilities include building SDTM datasets from raw EDC data, validating ADaM in R, producing TLFs and submission-ready datasets, with QC of SAS and R outputs, and collaboration on SAPs and timelines.