This position of Associate Director has responsibilities as a safety data scientist in Epidemiology Analytics group of Clinical Safety and Pharmacovigilance (CSPV) at Daiichi Sankyo. This position uses and analyzes both clinical trial data and real-world data (RWD) to support our products under the supervision of the head of Epidemiology Analytics. This position leads the development and implementation of statistical analysis plan to support signal detection and evaluation, risk-benefit assessment, and other drug safety evaluation activities. This position collaborates with internal and external stakeholders including statisticians, epidemiologists, clinical safety and pharmacovigilance, regulatory, clinical, and other project stakeholders. In this position, you will play a critical role in supporting Epidemiologist and Safety Science team during an evaluation of adverse events and assessment of potential risks associated with our pharmaceutical products. We are looking for a detail-oriented, experienced, resilient, and proactive individual with outstanding analytical and communication skills in the industry or service provider settings. If you are driven by a desire to make a positive impact on the enrichment of quality of life around the world, we encourage you to apply for this exciting opportunity. Responsibilities Provide data management of diverse data (e.g., real-world setting and clinical trial) to set up epidemiologic data sets for various approaches, quantitative epidemiologic data analysis, interpretation of results, visualization of results, and generate manuscripts to disseminate findings. Conduct statistical analyses for epidemiological research and safety queries, including but not limited to: o Descriptive summary and multivariable regression o Exploratory analysis for safety endpoints in clinical trial data o Setup and analysis of case-control and cohort study designs o Signal detection analysis in spontaneous reports (e.g., FAERS, EVDAS) o Signal detection/evaluation analysis in RWD o Data mining (including free-text mining of unstructured data fields) using diverse data sources and methods o Development of automation platform (e.g., R Shiny App) o Literature review and meta-analysis Collaborate with cross-functional teams to evaluate and manage adverse events and risks associated with pharmaceutical products. Participate in cross-functional meetings and provide input and guidance as needed. Participate in the preparation and submission of regulatory documents related to drug safety. Maintain and manage project plans to provide deliverables on time. Collaborate with global epidemiology teams to ensure consistency and quality in safety reporting and processes. Maintain compliance with all applicable regulations and guidelines related to pharmacovigilance and drug safety. Stay informed about emerging safety issues and contribute to the development of risk management strategies. Mentor and provide guidance to junior team members. Qualifications Education Qualifications. Master's Degree in Biostatistics, Data Science, Statistics, Applied Mathematics, Epidemiology, or related field plus 7 years of experience in epidemiologic methods and data analysis (pharmaceutical industry in safety or associated service provider experience is preferred) required PhD in Biostatistics, Data Science, Statistics, Applied Mathematics, Epidemiology, or related field plus 4 years of experience in epidemiologic methods and data analysis (pharmaceutical industry in safety or associated service provider experience is preferred) preferred. Experience Qualifications 3 or more years of professional experience within the pharmaceutical industry Demonstrated professional statistician skills and expertise Proven experience leading large and/or complex statistical programming projects preferred Experience providing technical and/or programming guidance and mentoring to junior programmers, fellows and team members. Ability and interest to work across cultures and geographies Ability to adapt to change and seamlessly assimilate to new projects and stakeholders Experience developing statistical analysis plan and Meta Data Repositories Familiarity with data management concepts of non-interventional studies Strategic thinking Demonstrate proficiency with programming in R, SAS, SQL, and/or Python for data mining and epidemiologic analysis Travel Requirements. Ability to travel up to 20% of the time. Both domestic and occasional travel may be required. Additional Information