Duties: Development and validation of new engine specific health monitoring functions, trend data cleansing scripts and their Portal interfaces; Support to development of engine model specific KPI dashboards; Analysis of engine operational data (from the field and test cell); Update of engineering process documentation; Engineering support for field engine investigations; Validation of new digital engine services as part of EIS roll out; Integration test support with aircraft OEMs
Requirements: Degree in Data Science, Machine learning, Aerospace Engineering

Duties: You will be working in the Oncology Biometrics Programming department reporting to a Sr. Director, Statistical Programming, providing leadership and management of standards governance activities at the therapeutic and study level related to the planning, execution and delivery of the data and the analysis reporting of clinical development. The scope of work includes, but is not limited to, the governance of clinical data standards change requests, development of new Oncology TA standards, and participation in cross-TA standards development activities
Requirements: Bachelor’s or Master’s (or local equivalent) degree in Mathematics, Statistics, Computer Science, Life or Social Sciences or related field; Support the Oncology Therapeutic Area Standards Definition Team by reviewing change requests from oncology study teams for standard components (with focus on SDTM, ADaM, TLF) to ensure compliance with the AZ & CDISC standards, regulatory guidelines and AZ Clinical data standards SOP, Protocol/SAP; Support study teams with questions related to oncology standards (with focus on SDTM, ADaM, TLF); Participate in and contribute to working groups (including SME’s) during review and optimisation of existing Corporate and Oncology Standards

Duties: As an Associate Director, you will apply advanced statistical and machine learning methods to analyze multi-modal data aiming to potential biomarker and MoA (mechanism of action) insights. You will drive the development of biomarker identification, validation and patient stratification strategies in collaboration with cross-functional teams. You will effectively communicate complex findings and recommendations to diverse stakeholders through compelling data visualizations, reports, and presentations. You will also work with our Research and Translational Medicine Leads to proactively influence the generation of data assets as part of a data generation strategy to evaluate novel hypothesis and drive target discovery
Requirements: PhD in Data Science, Statistics, Bioinformatics, Computer Science, or a related quantitative field, with more than three years of experience in Pharma/Biotech or large cancer center; Extensive expertise in statistical analysis, machine learning, and advanced data manipulation techniques; Proficiency in programming languages such as Python, R, or similar; Significant experience in cancer biomarker analysis of multi-modal data from oncology clinical trials; Deep knowledge of cancer genetics and key algorithmic & statistical methods applicable to cancer genomics