SDTM Automation Business Analyst

Job description:

The SDTM Automation Business Analyst bridges clinical data science, statistical programming, and IT engineering. You will lead the analysis, design, and optimization of automated pipelines that transform raw clinical trial datasets into CDISC SDTM (Study Data Tabulation Model) and ADaM regulatory submission formats. You will partner with biostatisticians, statistical programmers, and software engineers to scale machine-learning or rule-based automation tools that reduce manual mapping and validation effort.

Key Responsibilities

• Requirements & Process Analysis:
• Partner with Clinical Data Management and Statistical Programming teams to map current-state (As-Is) vs. future-state (To-Be) SDTM conversion and validation workflows.
• Translate complex clinical protocol requirements and CDISC standards into clear functional specifications, user stories, and acceptance criteria for automation platforms.
• Automation & Solution Design:
• Drive the design of automated data-mapping, translation, and conformance-checking tools (e.g., SAS, R, Python, or AI-driven pipelines).
• Identify bottlenecks in clinical data standards implementation and propose scalable, low-maintenance technology solutions.
• Validation & Compliance:
• Author, execute, and document System Development Life Cycle (SDLC) artifacts, validation plans, and User Acceptance Testing (UAT) scripts in compliance with FDA, EMA, and GxP standards.
• Ensure data integrity, traceability, and regulatory readiness for submission-ready SDTM datasets.
• Stakeholder & Vendor Management:
• Act as the primary liaison between clinical domain experts, IT engineering, and external technology vendors.
• Lead backlog grooming, sprint planning, and release coordination in an Agile/Scrum environment.

Qualifications & Requirements

Basic Qualifications

• Bachelor’s degree in Computer Science, Information Systems, Biostatistics, Bioinformatics, or a related scientific/technical field.
• 5+ years of experience as a Business Analyst, Data Analyst, or Technical Product Analyst within the biopharmaceutical, clinical research (CRO), or life sciences sector.

Preferred & Technical Skills

• CDISC Standards: Deep, practical understanding of CDISC SDTM, ADaM, and Define-XML standards.
• Technical Fluency: Familiarity with clinical programming languages (SAS, R, or Python) and clinical data management systems.
• Automation & Analytics: Experience working on data pipelines, ETL processes, or AI/ML-driven clinical data transformation initiatives.
• Regulatory Knowledge: Working knowledge of FDA/EMA electronic submission requirements (e.g., eCTD, Pinnacle 21 validation checks).
• Methodologies: Experience with Agile/Scrum tools (Jira, Confluence) and GxP system validation protocols.