Statistical Analytical Programmer

Slipstream IT

Statistical Analytical Programmer transforming real-world data into analysis-ready datasets at Slipstream IT. Collaborating with epidemiologists and biostatisticians for regulatory decision-making.

Posted 6/13/2026full-timeRemote • Pennsylvania • 🇺🇸 United StatesMid-LevelSeniorWebsite

ATS Keywords

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Hard Skills

SAS programmingdata analysisstatistical workflowsprogramming skills in Rquality controlpeer reviewdocumentation skillsdata transformationdataset derivationepidemiologic study designs

Soft Skills

attention to detailcollaborationcommunicationorganizational skillsproblem-solving

Tools & Technologies

EMREHRclaims dataregistriesVeeva Vaultdocument management systems

Industry Keywords

real-world dataobservational researchepidemiologybiostatisticsregulatory projectsFDA RWE guidanceSOPsaudit readinesstraceabilitycomparative effectiveness

Tech Stack

Tools & technologies

Vault

About the role

Key responsibilities & impact

Analyze real-world datasets to support epidemiologic, scientific, and regulatory projects
Build, validate, and maintain SAS programs for analysis datasets and study outputs
Transform raw real-world data sources including EMR, EHR, claims, and registries into accurate, traceable, analysis-ready datasets
Perform quality control and peer review to ensure programming deliverables are accurate and aligned with study plans and SOPs
Document programming decisions and dataset derivations to support reproducibility and audit readiness
Review and validate SAS code and outputs developed by other programmers
Partner with cross-functional teams including epidemiology, biostatistics, medical writing, regulatory, and client stakeholders
Follow internal SOPs, FDA RWE guidance, and other applicable regulatory standards

Requirements

What you’ll need

BS or MS in statistics, biostatistics, epidemiology, computer science, or a related quantitative field
5+ years of SAS programming experience in life sciences, ideally supporting observational research, epidemiologic studies, or regulatory projects using real-world data
Strong understanding of real-world data structures, especially EMR- and EHR-based datasets, as well as claims and registry data
Experience supporting retrospective cohort, natural history, burden of illness, comparative effectiveness, and other epidemiologic study designs
Strong programming skills in SAS, with R experience beneficial for data analysis, programming, and statistical workflows
Strong documentation skills, including code annotation, traceability, and reproducibility
Experience with Veeva Vault or similar document management systems is a plus

Benefits

Comp & perks

401k match
Comprehensive group health, dental, vision benefits
Life insurance/LTD
Discretionary PTO