Associate Director, RWE Statistics Programming

Overview:

Associate Director, RWE Statistics Programming

Overview

A global biopharmaceutical company on a mission to Solve On, Incyte follows science to find solutions for patients with unmet medical needs. Through the discovery, development, and commercialization of proprietary therapeutics, Incyte has established a portfolio of first-in-class medicines for patients and a strong pipeline of products in Hematology, Oncology and Inflammation and Autoimmunity

Headquartered in Wilmington, Delaware, Incyte has operations in North America, Europe, and Asia.
 

Job Summary (Primary function)

The Associate Director, RWE Statistics Programming is responsible for statistical programming that processes clinical trial and real-world data required for statistical analysis of Phase I–IV clinical trials, observational studies, and Medical Affairs real-world evidence (RWE) research/evidence generation activities. This role ensures the efficiency, timeliness, quality, and traceability of statistical programming deliverables, including outputs supporting scientific communications and HTA/payer-relevant evidence.

Essential Functions of the Job (Key responsibilities)

• Conduct statistical programming of clinical data and real-world data (RWD) using SAS.
• Generate analysis datasets according to CDISC standards and the Statistical Analysis Plan (SAP) (including ADaM where applicable).
• Implement analysis methods per SAP and produce tables, listings, and figures (TLFs), summary tables, graphs, and data listings using SAS.
• Conduct exploratory and ad hoc analyses to identify trends, patterns, and associations in RWE/RWD to address evolving questions.
• Support Medical Affairs evidence generation by delivering analysis-ready datasets and publication-quality outputs for internal insights and external dissemination (e.g., abstracts, posters, manuscripts, presentations).
• Provide programming support for RWE study deliverables used to inform medical strategy, scientific exchange, and stakeholder discussions.
• Program and QC HTA-aligned analyses using clinical and RWD sources to support payer and reimbursement evidence needs, including alignment to PICO and specific HTA expectations.
• Produce traceable comparative evidence outputs (e.g., baseline characteristics, treatment patterns, outcomes, subgroup analyses) suitable for HTA evidence packages and to support health economic modeling inputs.
• Implement and document HTA-relevant analytic methods as appropriate (e.g., propensity score matching/weighting, balance diagnostics such as standardized mean differences, time-to-event and longitudinal outcome analyses) with clear validation/QC.
• Ensure programs, outputs, and documentation are consistent with ICH guidelines and conducted in compliance with company SOPs and applicable regulatory expectations (including electronic submission standards).
• Validate programs and associated results produced by other programmers; perform independent QC to ensure accuracy, reproducibility, and high-quality deliverables.
• Run and review CDISC validation programs (e.g., OpenCDISC-style reports) to ensure datasets are CDISC-compliant; resolve findings and ensure clean validation summaries.
• Participate in the review of SAPs and other documents essential to the conduct of statistical programming work.
• Work with Clinical Research Organizations, as required, to participate in the oversight and management of programming activities to help ensure quality, timeline and deliverable are met.
• Work independently to program for individual projects and studies with minimum supervision.
• Review Production area after study programming is complete to make sure datasets, programs, and outputs are properly stored.
• Check that the validation summary reports are clean of errors and warnings and show proper documentation of SAS programs.
• Assist in the preparation of statistical reports, presentations, and publications, summarizing findings and providing insights to stakeholders.
• Conduct exploratory and ad hoc data analyses to identify trends, patterns, and associations in real-world data.
• Assess resource needs and to ensure projects are adequately resourced.

Qualifications (Minimal acceptable level of education, work experience, and competency)

• BA/BS degree (MS degree in statistics or computer sciences is desired) or relevant experience and equivalent qualifications will also be considered
• Minimum 8 years of programming experience using SAS/Base/Macro/GRAPH in the biopharmaceutical and/or CRO industries
• Experience supporting studies and analyses across Oncology, Hematology, and Dermatology therapeutic areas
• Experience supporting Phase I–IV clinical trials, including statistical programming for study deliverables across early- and late-stage development.
• Statistical Programmer with familiarity and hands-on experience working with Real-World Evidence (RWE) datasets, partnering closely with Medical Affairs teams to support evidence generation, analyses, and data-driven insights.
• Data Management experience including CDISC standard is highly desirable.
• Strong SAS programming skills and attention to detail are essential.
• Demonstrate knowledge of regulatory guidelines, including electronic submission standards.
• Strong organizational, time management, communication and project coordination and leadership skills.
• Must be able to work well under timeline pressure.
• Must be able to work on multiple tasks while coordinating others at the same time.
• Demonstrate experience serving as a mentor to junior programmers and as an expert to provide recommendations and solutions to complex problems.

Disclaimer: The above statements are intended to describe the general nature and level of work performed by employees assigned to this job. They are not intended to be an exhaustive list of all duties, responsibilities, and qualifications. Management reserves the right to change or modify such duties as required.

Incyte Corporation is committed to creating a diverse environment and is proud to be an equal opportunity employer.

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