4 days left
- Experience Level
- Experienced (non-manager)
Develop statistical methods sections of protocols and review case report forms (CRFs). Prepare analysis plans and write specifications for analysis files, tables, and figures. Communicate with clients regarding study protocol or statistical analysis issues as they arise. Communicate with study team members regarding study execution as it relates to timelines, data quality, and interpretation of results. Interpret analyses and write statistical sections of study reports. Accountable for controlling costs and maximizing revenue recognition. Provide training, guidance and mentorship to lower level and new staff.
• Production of High-Quality Deliverables: Completes and reviews more complex assigned tasks with a focus on accuracy. Conducts all appropriate validation requirements, according to Standard Operating Procedures (SOPs), for each task undertaken. Checks programming logs for cleanliness and correct processing of data. Inputs into Data Issues log and follows issues to appropriate resolution.
• Leadership: Perform statistical team lead role on single studies. Through this, works closely with the Project Team Lead and supervisor to deliver on time, with high quality and within budget. Build and maintain effective customer relationships, driving statistical discussions, providing support and/or guidance for statistical activities. Demonstrates and promotes efficient communication. If in lead role, runs meetings, documenting where necessary and following up on actions. Actively participates in internal project team meetings, provides timely progress updates. As a lead, will have input on estimate at completion (EAC) reporting.
• Data Management: Assist in reviewing or advising data management staff on database design, validation checks and critical data. Handles data issue resolutions. If in lead biostatistical role, handles lock and unblinding process with appropriate supervision.
• Statistical Analysis Plan (SAP) and Shells: Authors or performs quality control review (QC) of SAPs and shells. Make best use of resources and expertise within the organization (e.g. Libraries, templates and consultants for complex statistical methods). May author or QC complex SAPs, under supervision if needed.
• Datasets: Writes and maintains programming specifications. Programs assigned datasets to industry standards. Handles dataset derivations and assignment.
• Tables, Listings and Figures (TLFs): Writes programming specifications for statistical analyses outputs. Programs TLFs, maximizes programming efficiency with use of tools, where applicable. Checks resulting output for format and content, and questions specification as needed. Ensures consistency across items produced.
• Timelines: Plans and documents timelines, forecasts resource needs, suggests work may be out of scope.
• Financials: Shares accountability (with resource managers) for the financial success of assigned studies. Accountable for controlling costs and maximizing revenue recognition. Responsible for sharing budget expectations with the team. Raises concerns to manager if new work or rework appears to be out of scope. Understands 'scope of work' and has an awareness of contract and budget assumptions.
• Knowledge Sharing: Helps train staff regarding operational items. Mentors junior staff. Supports colleagues and provides motivation as needed.
• Risk Management: Identifies risks to project delivery and/or quality and spends time to proactively avoid as well as proposes solutions to mitigate risks. Where possible, anticipate risks to minimize need for study level escalations.
• Other Clinical Data Interchange Standards Consortium (CDISC) requirements: Leadership: Under supervision within Compound. May perform statistical team lead role on studies within a compound. In addition to the leadership responsibilities above, also prioritizes and takes proactive approach to gain efficiencies in work across protocols.
• Study Start up: Assist with protocol development, sample size calculation, protocol and case report form (CRF) review.
• Protocol: Authors or performs quality control (QC) review of the statistical section of a protocol (making best possible use of resources and expertise within the organization (e.g. Libraries, templates and consultants for complex statistical methods).
• Proposals: May be able to review and comment on proposals/budgets at a study level. May contribute to request for proposals (RFP). May be expected to present at bid defenses.
• Clinical Study Report (CSR): Reviews or drafts CSR or statistical report.
• Customer: On occasion, may serve as primary point of contact for customer. May also consult on operational topics with clients.
• Lock and Unblinding Process: Handles the database lock and unblinding process. May participate on the biostatistics randomization team (drafts randomization specifications and/or reduce or perform quality control (QC) review of randomization schedules). May serve as unblinded lead statistician.
• Other Responsibilities: As defined on ad-hoc basis by managers. May assist with cross functional collaboration.
• Bachelor's Degree Biostatistics or related field and 3 - 5 years relevant experience Req Or
• Master's Degree Biostatistics or related field and 3-5 years relevant experience Req Or
• Ph.D. Biostatistics or related field and 1 year relevant experience Req
• Typically requires 3-5 years of prior relevant experience, or equivalent combination of education, training and experience.
• Requires advanced knowledge of job area, and broad knowledge of a other related job areas, typically obtained through advanced education combined with experience.
• Excellent written and oral communication skills including grammatical/technical writing skills.
• Excellent attention and accuracy with details.
• In-depth knowledge of applicable clinical research regulatory requirements, i.e., Good Clinical Practice (GCP) and International Conference on Harmonization (ICH) guidelines.
• Familiarity with moderately complex statistical methods that apply to applicable clinical trials.
• Strong individual initiative.
• Strong organizing skills.
• Strong working knowledge of SAS computing package.
• Familiarity with other relevant statistical computing packages such as nQuery.
• Strong commitment to quality.
• Ability to effectively manage multiple tasks and projects.
• Ability to lead and co-ordinate small teams.
• Ability to solve moderately complex problems.
• Ability to establish and maintain effective working relationships with coworkers, managers and clients.
• Working knowledge of relevant Data Standards (such as Clinical Data Interchange Standards Consortium CDISC/ADaM).
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