Senior Principal Statistical Programmer

Job Description

Major accountabilities: Lead statistical programming activities for several studies or drive the implementation of data analytics reports -Make decisions and propose strategies at study or project level. May act as functional manager for local associates including providing supervision and advice on functional expertise and processes. Build and maintain effective working relationship with cross-functional teams, able to summarize and discuss status of deliverables and critical aspects (timelines, scope, resource plan), e.g. as representative in study or project-level team. Ensure project-level standardization -Provide and implement programming solutions; ensure knowledge sharing. Act as expert in problem-solving aspects. Ensure timely and quality development and validation of datasets and outputs for regulatory submissions/interactions, safety reports, publications, post-marketing activities etc -Leads/coleads novel projects within the team -Generates innovative ideas within own team and /or project team /functional community -Recognizes and leverages innovation opportunities for own team across projects -Mentors and inspires others to solve problems -Reporting of technical complaints / adverse events / special case scenarios related to Novartis products within 24 hours of receipt -Distribution of marketing samples (where applicable) Key performance indicators: Achieve high level of quality, timeliness, cost efficiency and customer satisfaction across functional activities and deliverables. Adherence to Novartis policy and guidelines -Customer / partner feedback and satisfaction Minimum Requirements: Work Experience: Biostatistics. Clinical Research Phases. R&D Portfolio Management. Statistical Programming. Data Management & Systems. Regulatory Submissions. Innovative & Analytical Technologies. Clinical Trial Design, Data Review & Reporting. Skills: Classification Systems. Clinical Trials. Computer Data Storage. Computer Programming. Cross-Functional Teams. Data Analysis. Data Structures. Initiative. Programming Languages. Reporting. Statistical Analysis.