Sr. Director, Product Management - Biostatistics SME

Apptad’s client is an AI and advanced analytics company serving the life sciences industry through clinical and commercial data platforms, AI capabilities, and analytics solutions. The Sr. Director of Product Management will own the strategy, roadmap, requirements, integration, validation, and release execution for the Navigator product series and its integration with BRAIN and related clinical AI capabilities.

Responsibilities:

• Own the product vision, strategy, roadmap, release scope, and backlog for SDTM, ADaM, and TLF Navigator products, including their transition toward an integrated and modular Navigator-X platform
• Define an end-to-end statistical-programming workflow covering protocol and SAP interpretation, source-data assessment, SDTM mapping, ADaM derivations, TLF specifications, program generation, execution, QC, traceability, approval, and reuse
• Serve as the statistical-programming and clinical-data product authority, ensuring product capabilities reflect how standards leads, statistical programmers, QC programmers, study leads, and programming-operations leaders perform their work
• Translate customer and internal stakeholder needs into product requirements, workflow diagrams, epics, user stories, acceptance criteria, release priorities, and measurable product outcomes
• Define MVP and MVP+ scope by balancing architecture, governance, user experience, existing customer workflows, technical feasibility, and longer-term product strategy
• Protect continuity for existing users while introducing conversational, natural-language, and agent-assisted workflows. Determine when the current user experience should be enhanced and when new workflow components are required
• Drive product capabilities involving protocol, SAP, mock-shell and source-data amendments; incremental predictions; historical-study reuse; standards-based specification generation; codelist prediction; reference files; artifact versioning; draft management; and out-of-sync detection
• Own requirements for SDTM and ADaM specification generation, direct ingestion of specifications and datasets, define.xml-related workflows, P21 and CDISC CORE validation, program generation and execution, concurrent job processing, lineage display, citations, and observability
• Define TLF Navigator capabilities for interpreting SAPs and mock shells, recommending required outputs, linking outputs to ADaM data and analysis methods, generating specifications and programs, supporting amendments, and checking consistency among SAP text, specifications, code, and final tables, listings, and figures
• Ensure the unified platform supports configurable SDTM, ADaM, and TLF stages so that each tenant can adopt one or more components without requiring an all-or-nothing implementation
• Own the Navigator-to-BRAIN integration model, including the controlled transfer of approved specifications, mappings, programs, datasets, outputs, metadata, and reusable assets into BRAIN for execution, QC, versioning, workflow management, and approval
• Define BRAIN requirements for study and standards setup, metadata management, artifact inventories, production and QC workflows, bulk status changes, dataset comparison, dry runs, version holds, execution scheduling, log parsing, audit trails, dependency analysis, and role-based operational dashboards
• Ensure the product supports variable-level traceability from raw data through SDTM and ADaM derivations to analysis results and TLF outputs, including the applicable specifications, programs, execution logs, versions, approvals, and QC evidence
• Define requirements for SAS and R execution, hybrid or sponsor-controlled compute environments, dependency management, analysis-object handling, automated log review, exception management, and selective re-execution of affected artifacts
• Establish the appropriate division of responsibilities between Navigators, BRAIN, Agent OS, and adjacent AI capabilities. BRAIN must remain the governed system of record while agents provide reasoning, orchestration, recommendations, and automation within controlled workflows
• Embed explainability, transparency, reproducibility, testability, human control, and observability into every AI-enabled workflow. Define requirements for citations, input and output traceability, model and token monitoring, cost monitoring, approval checkpoints, and exception handling
• Ensure AI-generated specifications, mappings, derivations, programs, summaries, and recommendations are reviewable, reproducible, version-controlled, and connected to deterministic SAS or R execution where numerical results are produced
• Lead product validation planning, including AI/ML validation, GxP assessment, UAT, validation evidence, defect classification, CAPA execution, audit readiness, and closure of findings before production release
• Partner with Architecture and Engineering on platform simplification, modularity, cloud portability, configuration management, maintainability, security, scalability, performance, and elimination of unnecessary technical complexity
• Define authorization requirements for study, portfolio, production, QC, blinded, and unblinded access, including group-based and individual security models and permission inheritance when an agent acts on behalf of a user
• Lead product and integration gap assessments, code walkthroughs, current-state versus target-state analysis, migration planning, hosting assessments, effort estimates, implementation costs, and release-readiness reviews
• Coordinate dependencies across Product, Architecture, Engineering, Quality, Implementation, Statistical Programming, Standards, Cloud Operations, Security, and Customer Success teams
• Own release governance across the Navigator and BRAIN ecosystem, including roadmap approvals, dependency tracking, resource requirements, sprint and scrum coordination, scope control, release documentation, validation status, and production readiness
• Support sandbox and pilot deployments by defining capabilities, entry and exit criteria, data and environment requirements, validation boundaries, success measures, issue-management processes, and the path from evaluation to validated production
• Conduct customer discovery, workflow reviews, product demonstrations, roadmap discussions, design sessions, and feedback workshops with statistical programming and biometrics leaders
• Convert recurring customer requests into scalable product capabilities while preventing one-off customization from creating inconsistent workflows, unsupported product variants, or long-term maintenance risk
• Develop product briefs, pre-reads, roadmap presentations, workflow documentation, integration plans, release notes, training materials, value propositions, and executive decision documents
• Define credible productivity and quality measures such as specification-development time, amendment-processing time, programming cycle time, QC effort, reuse, exception rates, traceability completeness, and time from source data to approved output

Requirements:

• Bachelor's or master's degree in Statistics, Biostatistics, Computer Science, Life Sciences, Data Science, Engineering, or a related discipline
• At least ten years of experience in pharmaceutical, biotechnology, CRO, clinical technology, or regulated software environments
• At least five years of product-management, product-owner, solution-management, or platform-leadership experience involving clinical data or statistical programming
• Strong understanding of the end-to-end statistical-programming lifecycle from raw data and protocol requirements through SDTM, ADaM, TLFs, QC, and submission deliverables
• Practical knowledge of CDISC SDTM and ADaM standards, controlled terminology, define.xml, metadata repositories, specifications, derivations, and standards-governance processes
• Understanding of SAPs, mock shells, TLF specifications, analysis populations, statistical methods, traceability requirements, and program-development workflows
• Working knowledge of SAS, R, programming logs, execution environments, program dependencies, production and QC processes, and output validation
• Hands-on programming is strongly valued but not mandatory
• Experience defining complex product requirements, workflow diagrams, PRDs, epics, user stories, acceptance criteria, roadmaps, and release plans
• Experience integrating products through APIs, services, metadata exchanges, workflow orchestration, or agent-based architectures
• Knowledge of AI/ML product development, including human-in-the-loop controls, explainability, reproducibility, evaluation, observability, model risk, and validation
• Experience with GxP, computerized-system validation, data integrity, audit trails, controlled change, CAPA, and inspection or audit readiness
• Ability to evaluate functional requirements alongside architecture, security, performance, usability, scalability, implementation effort, and commercial value
• Strong facilitation and communication skills with the ability to translate between statistical programmers, business users, product teams, architects, engineers, quality teams, and executives
• Demonstrated ownership of cross-functional initiatives from discovery and business case through development, validation, deployment, and adoption
• Prior experience as a statistical programmer, standards lead, statistical-programming lead, biometrics product owner, or clinical data-platform leader
• Experience with SDTM or ADaM automation, specification generation, program generation, TLF automation, metadata repositories, or statistical-computing platforms
• Familiarity with Pinnacle 21, CDISC CORE, SAS, R, Posit, Unix-based computing environments, cloud platforms, and sponsor-controlled execution models
• Experience implementing agentic AI, natural-language interfaces, knowledge graphs, MCP-based integrations, or AI-assisted clinical workflows
• Experience building multi-tenant products with configurable modules, role-based security, hybrid deployment, and validated production environments
• Experience supporting pharmaceutical sponsors or CROs through pilots, sandboxes, audits, validation, implementation, and enterprise adoption
• Understanding of submission programming, reporting events, interim analyses, database locks, dry runs, amendment impact, and regulated output production
• Bachelors or Master's degree in Computer Science, Information Technology or relevant field