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RWE Programmer (SAS)

Remote • Posted 6 hours ago • Updated 6 hours ago

Full Time

On-site

Fitment

Dice Job Match Score™

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Job Details

Skills

SAS/SQL
Data Analysis
Electronic Health Record (EHR)
Quality Assurance
Attention To Detail
Data Cleansing
Data Extraction
Reporting
Collaboration
Data Processing
Mathematics
Relational Databases
Research
Database
Pharmaceutics
Biotechnology
Analytical Skill
Communication
Documentation
Biostatistics
Computer Science
Statistics
Data Modeling
Clinical Data Management
CDISC
Python
Databricks
Cloud Computing
Analytics
Pharmaceutical Industry
Training
SAS
SQL
R
Health Care
Medicare
Epidemiology
Survival Analysis
Regression Analysis
Data Validation

SAS/SQL
Data Analysis
Electronic Health Record (EHR)
Quality Assurance
Attention To Detail
Data Cleansing
Data Extraction
Reporting
Collaboration
Data Processing
Mathematics
Relational Databases
Research
Database
Pharmaceutics
Biotechnology
Analytical Skill
Communication
Documentation
Biostatistics
Computer Science
Statistics
Data Modeling
Clinical Data Management
CDISC
Python
Databricks
Cloud Computing
Analytics
Pharmaceutical Industry
Training
SAS
SQL
R
Health Care
Medicare
Epidemiology
Survival Analysis
Regression Analysis
Data Validation

Summary

Job Summary:
We are seeking an experienced Real World Evidence (RWE) Programmer with strong SAS, SQL, and R programming expertise to support observational research and healthcare data analytics initiatives for pharmaceutical and biotechnology clients. The ideal candidate will have hands-on experience working with large-scale healthcare claims and Electronic Health Record (EHR) databases, developing patient cohorts, and creating high-quality analysis datasets for real-world evidence studies.
This role requires exceptional analytical and programming skills, attention to detail, and the ability to work independently in a fully remote environment.
Responsibilities:

Develop, maintain, and validate SAS programs to manipulate and analyze large healthcare datasets.
Design and create complex analysis datasets from multiple data sources.
Build patient cohorts and evaluate healthcare events using observational research methodologies.
Perform data cleaning, validation, and quality checks to identify outliers and ensure data accuracy.
Write efficient SQL queries for data extraction, transformation, and reporting.
Collaborate with epidemiologists, biostatisticians, and cross-functional teams to support RWE studies.
Generate reports and documentation supporting research and analytics initiatives.
Ensure programming deliverables meet quality standards and project timelines.
Maintain clear documentation for programming logic, data processing, and validation activities.

Requirements:

Bachelor's degree in Computer Science, Statistics, Mathematics, Biostatistics, or a related quantitative field.
Minimum 4 years of SAS statistical programming experience.
Strong experience with SQL and relational databases.
Hands-on experience with R programming.
Experience working with Real World Evidence (RWE) projects.
Strong understanding of observational research methods and epidemiology.
Experience creating patient cohorts and longitudinal healthcare datasets.
Experience with advanced statistical methods, including survival analysis and regression techniques.
Experience working with healthcare claims and EHR databases such as:
MarketScan.
Optum.
Medicare.
Prior experience directly supporting pharmaceutical or biotechnology companies is required.
Excellent analytical, communication, organizational, and documentation skills.

Preferred Qualifications:

Master's degree in Epidemiology, Biostatistics, Computer Science, Statistics, or a related discipline.
Experience working with the OMOP Common Data Model (CDM).
Knowledge of CDISC standards.
Experience with Python, Databricks, or other cloud-based analytics platforms.
Pharmaceutical industry programming experience.
dditional training or experience in epidemiological methods.

Required Skills:

SAS Programming
SQL
R Programming
Real World Evidence (RWE)
Healthcare Claims Data
Electronic Health Records (EHR)
MarketScan
Optum
Medicare Data
Patient Cohort Development
Epidemiology
Survival Analysis
Regression Analysis
Data Validation
Statistical Programming.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91116760
Position Id: 868ad28887886bca01b6f0bc36897118
Posted 6 hours ago

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