The position is responsible to support the PM leader or CPP leader who is the modeling lead in development and execution PK/PD Modeling and Simulation activities related to the research, design, implementation, data analysis, interpretation, reporting, and publication of CPP sponsored and -supported studies for products in any phase of development. The supports are mainly focused on data related and e-submission related aspects.
- We believe in applying scientific rigore to reveal the full promise inherent in data.
- We nurture intellectual curiosity and encourage everyone to approach new challenges with enthusiasm and the desire for discovery.
- We believe in collaboration and invite a diversity of perspectives, drawing on a variety of talents to create a wealth of possibilities.
- We prize innovation and seek intelligent solutions using leading-edge technology.
How you will contribute:
- Prepare programming scripts (e.g. R, SAS) to generate NONMEM analysis input dataset(s) for PK and/or PD analysis, based on requests from PM leader or CPP leader who is the modeling lead. During dataset generation, PM support also modifies the variable definition file (PM leader or CPP leader is the main author of this document) which clearly defines each variable within this dataset with any additional information as she/he sees fit. The NONMEM input dataset(s) to be created could be for interim or final analysis. The source used could be interim (uncleaned) or final SDTM/ADAM datasets or in sources in other formats, in some cases extensive data cleaning and complex calculation are needed.
- Upon request, QC NONMEM input dataset(s) generated by another PM support. Log which QC script is used, which subjects were checked per study, what other aspects were checked within the dataset, the findings of the QC and the follow-up actions of those findings in a QC document.
- Generate e-submission package for NONMEM analysis. In general, the package includes NONMEM input datasets, NONMEM control file, output parameter files, output table files and other files, in addition to supporting documents such as define and var-names-descr files. PM support renames the files provided by PM leader or CPP leader so they fit the naming convention requirements for e-submission package if needed, converts these files into the appropriate formats, and places them into the right folder structure then links them to the define and var-names-descr files. PM support works closely with EPOD team to ensure the e-submission package has the right structure, correct formats and being placed in the right assembly server directory.
- Provide guidance to new or junior members of the CPP community for the DataFlow process. The steps in the DataFlow process include but are not limited to: Kickoff meetings to outline the scope of work (e.g. PK and/or PD), timelines (e.g. before or after database lock) and support needed from other departments (e.g. Data Management (DM), programming, Bioanalysis (BAN)/ Biologics Development Science (BDS) etc); initiation, reviewing and signing off of tsDTA; setting up secured exchange medium; monitoring timeline during dataset preparation stage (e.g. if source datasets are delivered on time); answering questions from PK office vendor during dataset preparation stage; monitoring delivery (e.g. if datasets are delivered on time); reviewing received datasets and sending feedback/requests back for modification due to programming mistakes if needed.
- Provide guidance to new or junior members of the CPP community for the Data Collection Tools review process. Data collection tools include eCRF, diary (if applicable), lab requisition form (if applicable) and completion guidelines etc.
Interact with other departments (including but not limited to Data Management, Programming, BAN/BDS, EPOD) and external Vendors (including but not limited to PK office vendors) to communicate the needs of CPP in data collection, data formatting and data representation group discussion and cross departmental trainings if needed. Promote better understanding across different departments.
- Revise, update and create (if needed) SOPs, Job aids, templates, training materials for CPP internal processes and other cross departmental processes as needs arise
- Improve CPP internal processes in dataset creation, dataset QC (e.g. a standard QC R script with a checklist) and e-submission package preparation (e.g. R script which can automate the linking of documents).
- Support the needs of CPP community in Secure exchange medium set up
Qualifications
Here at Cytel we want our employees to succeed and we enable this success through consistent training, development and support. To be successful in this position you will have:
- Bachelor’s degree in one of the following fields Statistics, Computer Science, Mathematics, etc.
- At least 6 years of SAS programming working with clinical trial data in the Pharmaceutical & Biotech industry with a bachelor’s degree or equivalent. At least 4 years of related experience with a master’s degree or above.
- Study lead experience, preferably juggling multiple projects simultaneously preferred.
- Strong SAS data manipulation, analysis and reporting skills.
- Solid experience implementing the latest CDISC SDTM / ADaM standards.
- Strong QC / validation skills.
- Good ad-hoc reporting skills.
- Proficiency in Efficacy analysis.
- Familiarity with drug development life cycle and experience with the manipulation, analysis and reporting of clinical trials’ data.
- Submissions experience utilizing define.xml and other submission documents.
- Experience supporting immunology, respiratory or oncology studies would be a plus.
- Excellent analytical & troubleshooting skills.
- Ability to provide quality output and deliverables, in adherence with challenging timelines.
- Ability to work effectively and successfully in a globally dispersed team environment with cross-cultural partners.
Skills Required
- Bachelor's degree in Statistics, Computer Science, Mathematics, or a related field
- At least 6 years of SAS programming experience with clinical trial data in the pharmaceutical or biotechnology industry with a bachelor's degree, or at least 4 years of related experience with a master's degree or above
- Strong SAS data manipulation, analysis, and reporting skills
- Experience implementing current CDISC SDTM and ADaM standards
- Strong QC and validation skills
- Ad hoc reporting skills
- Proficiency in efficacy analysis
- Familiarity with the drug development lifecycle and clinical trial data manipulation, analysis, and reporting
- Experience with submissions using define.xml and other submission documents
- Study lead experience and ability to manage multiple projects simultaneously
- Experience supporting immunology, respiratory, or oncology studies
- Excellent analytical and troubleshooting skills
- Ability to deliver quality outputs within challenging timelines
- Ability to work effectively in globally dispersed, cross-cultural teams
Cytel Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Cytel and has not been reviewed or approved by Cytel.
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Healthcare Strength — Health coverage is described as comprehensive, spanning medical, dental, vision, life and disability, with FSAs/HSAs also available. Plan quality is often characterized as good to excellent, which lifts the perceived value of the overall package.
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Retirement Support — A 401(k) with employer match is consistently part of the benefits package. The plan is also characterized as well managed, contributing to a sense of baseline retirement support.
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Fair & Transparent Compensation — Overall pay is characterized as decent-to-good and broadly competitive in parts of the business, with stronger alignment noted in senior technical tracks like biostatistics and programming. The total package is often framed as respectable rather than premium.
Cytel Insights
What We Do
Cytel enables decision-makers in the life sciences to unlock the full potential of their products. From navigating uncertainty to proving value, Cytel’s 30 years of global expertise in consulting, data-driven analytics, and industry-leading software helps biotech and pharmaceutical companies transform intelligence into confident decisions. We have an uncompromising commitment to scientific rigor and high standards of operational excellence, which are channeled through our locations in North America, Europe, the United Kingdom, and Asia. Together, we enable our clients to deliver the therapies that propel humanity forward. Cytel employs a range of data science tools from biostatistics to machine learning to help executives in the life-sciences to make confident decisions powered by data. We are probably best known for being leaders in the field of adaptive clinical trial design, a subset of trial design that uses interim looks to enhance the patient safety and commercial value of pharmaceutical products. We also have specialists in Bayesian statistics, real world evidence, artificial intelligence, health economics, and a number of other research fields to ensure that academic and scientific findings can have impact on industry quickly and seamlessly. www.cytel.com








