Director, Statistical Programming

Vor Bio•Boston, MA

1d•Hybrid

About The Position

The Director, Statistical Programming will be responsible for performing data and statistical analysis in multiple clinical studies and collaborating with study statisticians, data managers and the other functions in the clinical study team. This is a senior individual-contributor role with no direct reports; the Director influences outcomes through cross-functional partnership and leadership, oversight of FSP programming resources, and mentorship of internal and external programmers. In this role you will provide strategical and technical leadership on clinical project teams, serving as the recognized statistical programming subject matter expert within the organization. Work is performed on the design, development, and quality control process for SAS programs used to access, extract, transform, review, analyze, and submit clinical data for individual studies. In addition, you will help lead departmental and cross functional technology development and process improvement initiatives, partnering with Biostatistics, Clinical Data Management, Clinical Operations and Sciences, Regulatory, and Pharmacovigilance to ensure all deliverables meet ICH, CDISC, and global health authority expectations.

Requirements

A Master degree in Statistics, Mathematics, computer science or other equivalents.
Minimum 12 years of SAS programming in a pharmaceutical, biotech or CRO setting, with at least 3 years in a senior/lead statistical programming role.
Expert-level knowledge in CDISC including SDTM, ADaM, metadata, controlled terminologies, and data flows, as well as in global industry standards for electronic submission of data to FDA, EMA, PMDA, and other health authorities.
Strong hands-on SAS programing skills and working experience for clinical trial reporting including SAS/STAT, SAS/GRAPH, SAS Macro, and SAS/SQL.
Demonstrated ability to lead and contribute to multiple clinical development programs simultaneously, including late-phase and registrational studies.
Prior experience as a statistical programming lead for at least one major regulatory submission (NDA / BLA / MAA) required; experience in rare or autoimmune disease strongly preferred
Proven experience managing CRO or FSP programming partners, including vendor selection, oversight, budget tracking, and issue escalation
Ability to be flexible and adapt quickly to the changing needs of the organization
Strong interpersonal and effective communication (oral and written) skills
Proven ability to lead and influence without direct authority, effectively mentoring and developing junior programmers and driving consensus across matrixed, global teams

Nice To Haves

Working knowledge of R, Python, or other modern analytics languages preferred, experience with programming automation and efficiency tooling a plus

Responsibilities

Serve as a study and program-level programming lead across one or more indications accountable for end-to-end delivery of activities including review SAP, set up mock TFL, dry run, draft and final TFLs, and integrated summary of safety/efficacy (ISS/ISE) analyses across program lifecycle.
Collaborate with other functions for cross-functional deliverables i.e. Safety updates (DSUR/PSUR), Health Authority response packages, publications, and congress presentations, etc.
Effectively design and develop advanced SAS programs including macros and reusable utility libraries for efficiency and consistency across the program and department.
Lead the standardization and process improvement initiatives, including authoring and refining SOPs, work instructions, programming standards, and reusable macro libraries.
Serve as the statistical programming lead for regulatory submissions (IND, NDA, BLA, sNDA, MAA) and Health Authority interactions, including preparation of eCTD-ready SDTM, ADaM, define.xml, Study Data Reviewer's Guide (SDRG), Analysis Data Reviewer's Guide (ADRG), and response packages for FDA, EMA, PMDA, and other global authorities
Represent Statistical Programming during regulatory inspections and sponsor/CRO audits; ensure submission readiness, traceability, and 21 CFR Part 11 compliance across deliverables
Codes complex SAS programs (including Macro language, SAS/STAT and SAS/GRAPH) for applications designed to analyze and report complex clinical trial data and for electronic review, exchange, transformation, and submission of data in CDlSC SDTM and ADaM formats; consistently meeting program- and submission-level objectives
Establishes and performs quality control and secondary review of SAS code and output produced by other Statistical Programmers; defines QC standards for assigned programs.
Demonstrates expert-level knowledge of clinical development and medical data.
Solves complex clinical trial and cross-study reporting problems and has a proven technical proficiency and is recognized as the technical subject matter expert within the organization; works autonomously, helps set direction for others, and drives resolution of escalated issues across studies and programs.
Creates CDISC data sets by transforming various raw data sources, including different Electronic Data Capture (EDC) databases and Interactive Web Response Systems (IWRS), tables, figures, and listings reporting and submitting the results of clinical trials for investigational medications, ensuring end- to end traceability and data integrity for source to submission.
Works with all types of coding dictionaries (MedDRA and WHODD) commonly used by the pharmaceutical industry
Works in a matrixed team environment providing technical leadership across statistical programmers and FSP resources without direct line management, and solving clinical trial reporting problems within budget and customary timeline constraints while assuring high quality standards
Contribute to long-range Statistical Programming strategy, including evaluation of emerging technologies (e.g., R/Python integration, open-source tools, automation), programming infrastructure, and organizational scaling in support of the portfolio
Mentor and develop internal programmers through informal coaching, code review, and sharing of best technical practices (no direct-report responsibility)
Represent Vor externally at industry forums (e.g., PHUSE, PharmaSUG, CDISC) as appropriate, contributing to the advancement of statistical programming practice in rare and autoimmune disease development