Associate Director, Translational Data Science

vor 3 Wochen

Munich, Deutschland AstraZeneca Vollzeit

**ABOUT ASTRAZENECA**

AstraZeneca is a global, science-led, patient-focused biopharmaceutical company that focuses on the discovery, development and commercialisation of prescription medicines for some of the world’s most serious diseases. But we’re more than one of the world’s leading pharmaceutical companies.

**SITE DESCRIPTION**

Welcome to Computational Pathology Munich, one of over 400 sites here at AstraZeneca, providing a collaborative environment where everyone feels comfortable and able to be themselves is at the core of AstraZeneca’s priorities, it’s important to us that you bring your full self to work every day. To help you maintain your best self, here’s a sneak peek into some of the things this site provides for you: After-work events, lunch & learns, spacious environment, sustainable office working environment, events, family and childcare support and of course the Alps around the corner for hiking, biking and skiing.

**BUSINESS AREA**

From diagnosis to later stage development, we’re laser-focused on leading the way forward to create solutions that transform lives. We are focused on identifying and treating patients earlier, where there is greater curative potential. With the greatest number of early stage cancer trials in the industry, we are getting closer to finding cures every day. It is the breadth and strength of our innovative pipeline that offers both security and stability. And with the goal to deliver 6 new molecular entities by 2025, it’s up to each of us to keep pushing our industry-leading Oncology pipeline forward and build the future

With pace and drive, comes trust that we will get it done. Embrace the freedom to create and expand your horizons. Always backed and supported by pioneering leaders, this is the place to build a world-class career that’s meaningful and rewarding. Here we’re on a journey to becoming digitally enabled, to discover new ways of offering better solutions to our patients. Join the team with a vision to use data as a tool, to build a better, deeper, more personal understanding of the people we’re helping. To ultimately deliver better outcomes for them - through dynamic omnichannel content, personal relationships, and experience.

**What you’ll do**
- Generate tissue biomarker data to guide indication selection and identification of targeted patient populations and deliver biomarkers for clinical studies based on the best available computational pathology technologies
- Lead a cross-functional team of Data & Translational Scientists, Digital Pathologists, AI Engineers, and Software and Product Developers to implement strategic vision that enables target identification, indication selection, early indication of biological activity and patient stratification/selection in Oncology
- Work with our bench scientists to proactively influence the generation of data assets as part of a data generation strategy.
- Share code and train peers and bench scientists in the tools critical to interpreting complex data.
- Conduct scientific project meetings to follow progress and present the scientific progress in Translational Medicine leadership meetings, governance boards and in project team meetings and ensure the quality of Translational Medicine clinical study reports, data reviews and interpretations, presentations, scientific publications and recommendations to development teams and management
- Lead and champion new innovations within own discipline and assess existing processes and workflows for ongoing technology and/or workflow improvements which will aid the department to meet overall strategic objectives.

**Essential for the role**
- PhD in Biological Sciences, Computational Biology, Bioinformatics, and/or related fields.
- Expertise in one or more of the following; Analysis of images (particularly from histopathology); a deep understanding of the molecular mechanisms driving cancer or immunological disorders; data management (including curation, data engineering, FAIR and reproducible research practices)
- Experienced at working on data analysis methods (using e.g. Python/R) in an academic or pharma research environment and applied knowledge on clinical biostatistics e.g. survival analysis, correlation, feature selection, cross-validation and visualization.
- Experience contributing to the research community through publication, conferences, and open-source code projects.
- Strong leadership and oral/written communication skills, interpersonal skills, and ability to multi-task a dynamic portfolio of drug projects and a robust technology development capability.
- Strong publication record and proven communication and presentation skills to wide audience (specialists and non-specialists).
- Excellent problem-solving skills with clear understanding of the balance of innovation, smart risks, fit-for-purpose solutions, and timely project delivery
- Ability to drive, influence, manage, execute, and deliver results for complex multi-fun

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