Our client is a leading biotechnology company that discovers, develops, manufactures and commercializes medicines to treat patients with serious or life-threatening medical conditions. They are among the world's leading biotech companies, with multiple products on the market and a promising development pipeline. Role Overview: The Data Analytics Leader Early Clinical Development (ECD) Data Intelligence team supports ECD study teams by delivering timely and high-quality analysis and real-time interactive visualizations. The DAL is an expert in data analysis and data insights, enabling the stakeholders to efficiently and effectively review and interpret data. The DAL works directly with ECD Clinical disease area leads, study team Clinical Scientists, and other line function colleagues to ensure that indication or disease specific scientific questions are explored thoroughly using creative data analysis and data visualizations through collaboration and innovation. The DAL is also responsible for aligning analytical data visualization and data analysis with other line functions. The DAL innovatively develops the tools and processes that are fit-for purpose and create maximum impact to the organization. The DAL manages the creation and implementation of analytical solutions and tools for ongoing medical review and Risk Based Quality Management (RBQM). The DAL provides training and dedicated support. The DAL offers continuous knowledge sharing and improvement of best practices for study teams to follow. The DAL participates and contributes to global cross-business unit workstreams (e.g., RBQM workgroup) representing ECD. Primary Responsibilities: • Strategically use internal and external data, develop advanced analysis data tables and data visualizations that fit for gRED ECD purpose. • Act as a main point of contact for Therapeutic Area (TA) leads or disease area leads with questions on specific disease area data exploratory analysis needs. • Collaborates within ECD and other line functions to align and simplify processes that prevent redundancy in analytics, and facilitate speed up the data driven decision. • Collaborate with the global RBQM workgroup to drive the design and improvement of technology and analysis solutions necessary for RBQM implementation, including in-house systems and potential external technologies. • Creates derived datasets from raw clinical trial data to support statistical analysis and reporting. • Analyze data for meaningful trends, trigger mitigating actions, and identify potential issues for knowledge sharing across studies. • Write detailed specifications for datasets, tables, and analyses based on clinical and regulatory requirements. • Develop and maintain standard macros, reusable functions, and tools to improve efficiency and ensure compliance with industry standards. • Use strong technical expertise and skills to find opportunities for innovation, efficiency and simplification with the mindset of working smarter. • Strong interpersonal skills and the ability to navigate in a complex, international, and matrixed environment. • Provide guidance and training and consultation for stakeholders on the analytical visualization tools to promote medical review and RBQM efficiency and best practices. • Ensure inspection readiness for the ECD specific analysis solutions. Qualifications: • Bachelors degree in Data Science, Statistics, Computer Science, Life Sciences, Public Health, or a related field. Masters degree preferred. • 5+ years experience in clinical trial data analysis, visualization or statistics in Biotech/Pharmaceutical industry. • Experience with early phase and Oncology clinical trials highly preferred. • 5+ years of experience in creating SDTM, ADaM, and developing TFL using SAS or R/RShiny. • 2+ years of experience in RBQM / RBM processes preferred, including awareness of industry strategy and direction, knowledge and understanding of ICH E8 and ICH E6 requirements. • Strong proven experience using data driven methods to analyze and solve business situations, strong critical thinking and analytical skills and aptitude for data analytics including mathematical and statistical concepts (hypothesis testing, regression analysis, data modeling). • Strong systems awareness including good knowledge of data pipelines, models and systems along with strong cross-functional inputs and dependencies contributing to end-to-end analysis solutions. • Able to multi-task and re-prioritize work on short notice, able to lean in and manage through change. • Track record of establishing successful partnerships across the organizations. • Excellent written and verbal communication skills and strong project management skills.