RWE Statistical Programmer

Role: RWE Statistical Programmer 

Job Location: Remote

Notice Period: Immediate

Experience: 6-15 Years

Skills: RWE ,SDTM, ADAM.

Role Summary

The RWE Statistical Programmer supports Real-World Evidence (RWE) studies by programming, processing, and analyzing Real-World Data (RWD) from sources such as claims, EHR/EMR, registries, and other observational datasets. The role focuses on building analysis-ready datasets, producing high-quality statistical outputs (TLFs), and ensuring end-to-end traceability and quality control to support publications, regulatory submissions, label expansions and internal evidence generation.

Key Responsibilities

· Program and maintain RWE study datasets from raw RWD sources (claims, EHR/EMR, registries, etc.).

· Perform data cleaning, standardization, reconciliation, and data quality checks.

· Develop cohort selection logic including inclusion/exclusion criteria, index date, baseline and follow-up periods.

· Derive analysis variables such as treatment exposure episodes, persistence/adherence (PDC/MPR), comorbidity indices (Charlson/Elixhauser), and outcomes.

· Support statistical analyses under the guidance of statisticians/epidemiologists (descriptive analyses, regression models, time-to-event analyses).

· Implement methods such as propensity score matching/weighting/stratification, subgroup and sensitivity analyses (as required).

· Generate Tables, Listings, and Figures (TLFs) for study reports, manuscripts, HTA submissions, and internal evidence packages.

· Create patient attrition flow diagrams, treatment pathways, and utilization trend summaries.

· Perform independent QC of datasets, programs, and outputs; document findings and resolutions.

· Maintain programming documentation including specifications, QC checklists, logs, and version control artifacts.

· Ensure compliance with SOPs, data privacy requirements, and audit readiness standards.

· Collaborate with cross-functional stakeholders (Biostatistics, Epidemiology, HEOR, Medical, Data Management).

· Develop reusable macros/functions to improve efficiency and standardization across studies.

Required Qualifications

· Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Life Sciences, or related field.

· Overall, 12 – 15 years of experience in statistical programming with 3+ years of hands-on statistical programming experience in RWE or observational studies.

Key Skills

· Strong SAS programming skills (DATA step, PROC SQL, SAS macros; PROC REPORT/MEANS/FREQ/PHREG/LOGISTIC as applicable).

· Experience handling large datasets and performing complex derivations and cohort logic.

· Good understanding of observational study design and real-world data limitations (bias, confounding, missingness).

· Familiarity with CDISC standards (SDTM/ADaM) and/or custom RWE data models.

· Knowledge of healthcare coding systems such as ICD-9/ICD-10, CPT/HCPCS, NDC, LOINC, SNOMED (as applicable).

· Good communication skills and ability to work in cross-functional teams.

· Experience in R programming (e.g., tidyverse, survival, MatchIt, tableone) is preferred.

· Hands-on experience with propensity score methods, survival analysis, and advanced regression models.

· Experience working with databases and cloud platforms (SQL, Snowflake, Databricks, AWS/Azure).

· Exposure to publication-ready output development and Regulatory/HTA submission deliverables.

Location : Remote

Suitable Candidates can share the resume to my mail ID [Confidential Information] for an immediate response.

Regards,

Priyadharshini.C

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