Director/Senior Director of Statistical Science - Statistical Innovation
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Director/Senior Director of Statistical Science - Statistical Innovation Location: Cambridge or Macclesfield (UK) Gaithersburg, Durham, Waltham, Wilmington (US) Gothenburg (Sweden) Mississauga (Canada) Or Barcelona (Spain) DescriptionDo you have a passion for developing and aiding implementation of innovative statistical approaches and methods in clinical studies? Are you up for the challenge to impact a company that follows the science and turns ideas into life changing medicines? If yes, we welcome you to join AstraZeneca! At AstraZeneca, we put patients first and strive to meet their unmet needs worldwide, while applying groundbreaking approaches to science across many business areas. Working here means being entrepreneurial, thinking big and working together to make the impossible a reality. If you are swift to act, confident to lead, willing to collaborate, and curious about what science can do, then you're our kind of person.We are recruiting a Statistical Science Director to join our growing Statistical Innovation group. Our main focus is providing statistical methodology support for all phases of clinical development for AZ's Cardiovascular, Renal & Metabolism and Respiratory & Immunology divisions together with specific targeted support for the Oncology division and the newly acquired Alexion division of AZ which specializes in medicines to treat rare diseases. In this role, you will belong to the Early Biometrics & Statistical Innovation (EB&SI) department, where our data-centric focus helps us work efficiently and creatively to bring the right medicines to the right patients. Our teams use their expertise in statistics and programming to address drug development objectives and reduce uncertainty in product development, driving better business decisions with quantitative reasoning. As part of the Data Science & AI team, you'll use technology at the forefront of science in a creative environment, with the scope to develop new statistical ideas and apply them in your work. Main duties and responsibilitiesJoining a team of statistical methodology experts, you will provide key input as you work to find solutions to problems at critical stages in the drug development cycle. This is exciting and technically challenging work in a dynamic and constantly changing landscape. Your key focus will be on producing pragmatic solutions, often within a tight time scale where the emphasis will be to deliver first, then refine and develop your solutions thereafter.You will contribute to, or lead capability build in more than one of the following statistical areas:
- Design of early and late phase clinical studies: including group sequential and adaptive designs using both frequentist and Bayesian approaches.
- Methods to analyse data collected in real-time, Estimands, Missing Data, Subgroup and Biomarkers.
- PhD in Statistics or a related field, followed by extensive experience of independent academic research and/or clinical drug development
- Documented ability of delivering innovative statistical solutions in an applied environment (related to at least two of the following areas or being externally recognized as an expert in at least one of these areas): Design of early and late phase clinical studies: including group sequential and adaptive designs. Analysis of data collected in real-time (e.g. sensor data), Missing data and Estimands, Subgroups and Biomarkers)
- Strong knowledge of programming in R and/or SAS
- High level of competence in global and cross-skilled collaborative working
- Extensive track record of research and methodological development in Statistics, supported by scientific publications in first class statistical journals
- Desire to apply your scientific competence on practical problems, for the benefit of patients
- Knowledge / research experience in the other areas such as development of statistical methodology related to the analysis and interpretation of safety data, observational studies, meta-analysis, non-linear and mixed effect models.
- Broad awareness of statistical issues against the evolving scientific and regulatory landscape
Vacancy expired!