The Statistical Programmer will be responsible for the development, maintenance, and validation of aCRFs, as well as of specifications and statistical programming of SDTMs, ADaMs (or derived datasets, as applicable), Tables, Listings, and Figures (TLFs), and submission packages required for various purposes including, but not limited to, IDMCs, IAs, and CSRs. The Statistical Programmer will also support DM with data cleaning activities, use global SAS macros, participate to internal initiatives to increase efficiency of the statistical programming of SDTMs, ADaMs, derived datasets, and TFLs, and use Pinnacle 21 to validate SDTMs, ADaMs, and define.XMLs.
The Statistical Programmer will work collaboratively within Biostatistical study teams and across departments to produce deliverables of the highest quality possible, within agreed timelines and budget, and in conformance with applicable ICH guidelines, Pharmaceutical Industry standards and guidelines, Regulatory Authority requirements and guidelines, and Indero's SOPs and processes.
More specifically, the Statistical Programmer will:
- Adhere and promote company organizational values and related expected behaviors, follow company SOPs and processes for all deliverables, and ensure all trainings assigned to oneself are completed on time.
- Review the statistical programming scope of work and budget at initiation of clinical trials and identify tasks that are out of scope.
- Support DM with data cleaning activities by programming, reporting, reviewing, and closing statistical data issues in collaboration with other Statistical Programmers and Lead Biostatistician.
- Develop/maintain/validate (as applicable) aCRFs according to protocol, eCRF, and Indero and/or Sponsor' standards and interpretation of CDISC SDTM IG and CT.
- Develop/maintain/validate (as applicable) specifications and Primary or QC statistical programming (as applicable) of SDTMs, ADaMs (or derived datasets, as applicable), and TLFs.
- Develop/maintain/validate (as applicable) SDTM define.XML/.PDF, cSDRG, ADaM define.XML/.PDF, and ADRG
- Validate SDTMs, ADaMs, and define.XMLs using Pinnacle 21
- Use global SAS macros to increase efficiency of the statistical programming of SDTMs, ADaMs, derived datasets, and TFLs.
- Contribute to the identification of future internal initiatives to increase efficiency/quality of Statistical Programming activities/deliverables and participate to the realization of these internal initiatives.
- Keep oneself abreast with latest Industry and CDISC standards as well as ICH and Regulatory Authority guidance and requirements.
May also:
- Act as a Lead Statistical Programmer on single studies.
- Review and provide input into SAPs, TLF Shells, and various DM documents (e.g., eCRFs, edit checks, etc.)
- Act as Unblinded Primary or QC Statistical Programmer for IDMCs and IAs.
- Coach more junior Statistical Programmers.
Education
- Bachelor’ degree in Statistics, Computing Sciences or a related field; Master’s degree an asset
Experience
- At least 1 years of clinical research experience in biotechnology, pharmaceutical or CRO industry, including 1 years of Statistical Programming.
Knowledge and skills
- Significant exposure to clinical trial data, SAP, TLF Shells, and specifications.
- Excellent working knowledge of SAS; SAS certification an asset.
- Knowledge of XML programming an asset.
- Good working knowledge of CDISC standards and guideline; CDISC certification an asset.
- Good knowledge of drug development process, ICH guideline (including but not limited to, ICH E6, E9, and E9(R1)), relevant HC and FDA regulations, guidelines, and electronic data submission requirements, and Pharmaceutical Industry GPP.
- Very organized and detail-oriented, with effective project planning and time management skills.
- Ability to work in high-speed environment with proven agility to juggle and prioritize multiple competitive demands.
- Must be able to work independently and as part of a team.
- Strong verbal and written communication skills in English
Top Skills
Innovaderm Research Montréal, Québec, CAN Office
3530 Boulevard St-Laurent, Suite 300, , Montréal, Quebec , Canada, H2X 2V1
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