R&D Executive - Statistician

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Job Brief:

The Clinical Biostatistics group is responsible for delivering leadership and expertise in the use of Statistics and Data Analytics across the Beauty & Wellbeing and Personal Care (BW & PC) Clinical Program. For Statistics this covers support in statistical design of clinical studies, statistical analysis, visualization of data and interpretation and reporting of results. Additionally, the group provides expertise in clinical data mining and modelling, and biostatistics support to the BWPC R&D cross functional teams with respect to the clinical program and related areas. The group delivers via a highly skilled team that is aligned to specific program areas within BPC and works in close partnership with Clinical researchers as well as BWPC Science & Technology (S&T), Global Design, Category Design, and Cluster Design teams on a global level.

Requirements & Qualifications: The candidate should ideally have at least a master’s degree in Statistics/Biostatistics, with three to six years’ experience in research or the FMCG/Pharmaceutical industries, although applications from less experienced candidates will be considered. Proficiency in SAS and R is essential, including the ability to automate routine tasks, develop macros, and build applications. Strong written and verbal communication skills are also required.

Responsibilities:
• Engagement and collaboration with globally deployed, multi-disciplinary teams to design and implement efficient, well-focused, statistically fit-for-purpose studies, analyse, visualise and interpret data.
• Work in inter-disciplinary teams that includes clinical study experts, measurement scientists, bioinformaticians, and other statisticians, both within Unilever and with external partners.
• Provision of statistical expertise across a range of R&D disciplines to define and implement statistical solutions.
• Deliver high quality statistical programming deliverables for all assignments that consistently meets study timelines, quality standards.
• Responsibility for the quality and defensibility of study designs, statistical analyses, models and data interpretation.
• Perform exploratory data analyses of clinical studies and reporting as required.
• Follow all standard practices as per SOP’s and guidance documents.

Key Accountabilities:
• Works as a member of a team to design and/or review protocols, case report forms, and other key study documents
• Write and review statistical sections and other relevant parts of study synopses and protocols
• Performs relevant sample size calculations
• Design randomization plans and generates random allocation lists
• Develops statistical analysis plans including analysis files and data reporting specifications
• Develops appropriate statistical methods for data analysis and ensures the accuracy and reproducibility of data sets and analyses of clinical study data
• Follows relevant work practices and procedures and organizational SoPs
• Working closely with mutli-disciplinary teams to ensure a complete review of the data, providing a thorough understanding of statistical processes and issues that may arise in analysis
• Plan the statistical analyses, programming and execution of the analyses, instructing and reviewing statistical planning and analysis work
• Perform hands-on data analysis and modeling of obtained data to provide outputs that will guide in decision making through various stages of project
• Liaises with other statisticians and scientists in areas of expertise and experience and ensures continuous improvement for themselves and the broader team via sharing of approaches and best practices;
• Provides statistical consultancy as required to the R&D programme.
• Engages and collaborates with globally deployed, multi-disciplinary teams to design and implement efficient, well-focused, statistically fit-for-purpose studies. Teams may include clinicians, measurement scientists, bio scientists, product formulators, claims experts, and others;
• Acts as secondary contact (supporting the Lead Statistician for the area) across multiple primary research areas (e.g. Skin Face Care, Microbiome, Skin cleansing, Hair Care, Oral, etc.);

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