On behalf of a Global Leader we are currently looking for a Biostatistician to join a long term contract which will be a mix between remote work and onsite in Southampton.

Role Objective

As part of the Data Sciences team this role requires mid-level experience, working in a dynamic multidisciplinary team to enable the delivery of one of the partners major programs. Key responsibilities include leading in providing statistical design support, data transformation and statistical analysis across a portfolio of projects to ensure robust data standards, efficient scientific data analysis and reporting.

Accountabilities

Lead statistical analysis for studies across functional areas.
Leading activities for development, maintenance and implementation of internal data standards and processes to ensure efficiency and traceability of data.
Providing statistical analysis and experimental design support across certain Sciences that includes clinical, pre-clinical and analytical chemistry data.
Contribute to data review and preparation to meet claims requirements and regulatory submissions.
Support projects with regards to study design and end-to-end data management to ensure consistency and traceability.
Provide SAS programming to support above tasks.
Ability to drive collaborative efforts cross-functionally and externally with outsourced vendors.
Key representative in interactions with internal stakeholders and cross-functional teams across Sciences and the R&D community and the wider business to ensure project delivery.

Essential Experience, Skills and Knowledge

Solid grounding in the application of statistical methods and data analysis.
Good working knowledge of data standards principles with emphasis on CDISC (STDM / ADaM).
Proficient in SAS Base Programming.
Proactive with strong interpersonal skills and ability to prioritise and organize tasks.
Good communication/interpersonal skills.
Cross functional working and leading projects to deliver on time in full.
Bachelor’s Degree or higher in Mathematics/Computing, Statistics, Biomedical Sciences, Life Sciences etc. with high data analytical content.
Thorough understanding of Analysis of Variance methods and awareness of modelling techniques.