Manager, Statistical Programming

Company: Daiichi Sankyo, Inc.
Location: Atlanta
Posted on: October 25, 2024

Job Description:

Join a Legacy of Innovation 125 Years and Counting!
Daiichi Sankyo Group is dedicated to the creation and supply of innovative pharmaceutical therapies to improve standards of care and address diversified, unmet medical needs of people globally by leveraging our world-class science and technology. With more than 125 years of scientific expertise and a presence in more than 20 countries, Daiichi Sankyo and its 18,000 employees around the world draw upon a rich legacy of innovation and a robust pipeline of promising new medicines to help people. In addition to a strong portfolio of medicines for cardiovascular diseases, under the Group's 2025 Vision to become a "Global Pharma Innovator with Competitive Advantage in Oncology," Daiichi Sankyo is primarily focused on providing novel therapies in oncology, as well as other research areas centered around rare diseases and immune disorders. - -
Summary
The purpose of this job is to oversee statistical vendor deliverables, perform programmatic review of analysis datasets and Table, Listing, and Figures (TLFs) generated by vendor, ensure deliverable quality, and expedite the preparation of oncology compound regulatory submission. It will also to maintain institutional knowledge across oncology compounds and support building up oncology programming standard on datasets and TFLs to improve efficiency and quality.Responsibilities- By leading internal programming contractor or by self, perform programmatic review of analysis datasets and TLFs generated by statistical vendor, ensure deliverable quality for the pivotal studies, Integrated Summary of Efficacy (ISE)/Integrated Summary of Safety (ISS) for oncology submission compounds, and expedite the preparation of regulatory submissions. Responsibilities include: review Case Report Form (CRF) annotation and Study Date Tabulation Model (SDTM) dataset, identify data inconsistencies and support data review, review analysis dataset specifications and ensure correct interpretation of SAP, develop independent programs to validate analysis dataset and TLFs generated by vendor, ensure analysis dataset in compliance with CDISC and submission requirement, review submission data package and ensure its quality and integrity- Oversee statistical programming vendor on project planning and execution to ensure high quality deliverables and timelines met. Responsibilities include: review and agree on vendor project timelines and resource planning, work in tandem with Biostatistics and Data Management members to ensure best vendor performance, monitor analysis dataset and TLFs transfers for ongoing and complete trials, confirm data use and output quality, proactively ensure the resolution of programming related issues prior to database lock analysis, be accountable and verify completeness of study programming deliverables, maintain all required study programming documentation required for Trial Master File (TMF)- Maintain institutional knowledge across oncology compounds and support building up oncology programming standard on datasets and TFLs to improve efficiency and quality. Responsibilities include: contribute to CRF and SDTM standard development, support develop, implement, and maintain Analysis Data Model (ADaM) dataset and TLF standard, develop sample programs to generate standard ADaM dataset and TLFs, support training and ensure implementation of ADaM and TLFs standard in clinical trials analysis- Provide programming support to prepare regulatory requested analyses and help submission team in quick turnaround in response to regulatory agencies. Responsibilities include: create TLFs to support submission QAs in a quick turnaround, support ad-hoc and exploratory analysis requested by clinical team, provide programming supports in agency response or potential Advisory Committee Meeting- Develop and maintain programming macros to effectively support internal data review and monitoring. Responsibilities include: work with Biostatistics member to define the requirements of efficacy data review, develop macros and support the internal data review and monitoring on an ongoing basis
Qualifications: Successful candidates will be able to meet the qualifications below with or without a reasonable accommodation.
Education Qualifications (from an accredited college or university)- Master's Degree Biostatistics or similar degree required- PhD Biostatistics or similar degree preferred
Experience Qualifications- 6+ Years of proven experience within pharmaceutical industry, or CROs supporting statistical analysis of clinical trials programming with a masters degree required- 3+ Years of proven experience within pharmaceutical industry, or CROs supporting statistical analysis of clinical trials programming with a PhD preferred- Advanced working knowledge of all aspects of the SAS programming language used in clinical trials programming. preferred- Advanced working knowledge of CDISC SDTM and ADaM, and extensive experiences of their implementation in clinical trials analysis preferred- Advanced understanding of statistical concepts in support of analyses and reporting of clinical trials. preferred- Having knowledge of all phases of drug development, including early and late phase clinical development and submission preferred- Having solid background of applied statistics preferred- Solid knowledge of new advanced statistical methods using SAS preferred- Knowledge in database structures and set-up preferred- The candidate should have successfully provided programming expertise at the Project level for at least two global development projects that have been submitted to regulatory agencies preferred
Travel
Ability to travel up to 10%
Daiichi Sankyo, Inc. is an equal opportunity/affirmative action employer. Qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected veteran status, age, or any other characteristic protected by law.

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