Director, Commercial Data Science

hace 1 mes

Madrid, España AstraZeneca A tiempo completo

**Make a greater impact on lives through a digitally-enabled enterprise**

We are working towards our aspiration of shaping the future of Pharma. Backed by investment at every step, we harness the latest technology, data, and innovative ways of working to introduce new approaches that put Digital at AstraZeneca’s heart.

Be part of a chapter that’s still being written. Trusted and empowered to change the way things are done, with the tools and support to get you there. Here we are free to unleash our curiosity and turn thinking into reality where smart risks and quick decisions come together to power disruption and innovation.

**Office Locations**: This is an on-site - office-based, global role. Please consider the following AZ HUB locations - Cambridge, UK - Madrid, Spain - Gothenburg, Sweden - Milan, Italy - Hamburg, DE.

**Role and Responsibilities**:
The **Director, of Commercial Data Sciences & AI** - European Union** is a key leader in the Commercial Data Science & AI team whose mission is to take a patient-centric, data-driven approach to personalize and transform healthcare delivery to the millions of patients along with a multi-disciplinary team of physicians who care for them. This responsibility involves working closely with cross-functional Science, Medical, and Business leaders to identify, prioritize, and develop Data Science, AI, and Advanced Analytics Platform & Products across AZ Oncology and Bio-pharma Business

The scope of this role is Global with a focus on EU markets where AstraZeneca’s life-changing medicines are approved to help patients live longer and realize AZ’s bold ambition of eliminating Cancer as a cause of death.

**YOUR MAIN ACCOUNTABILITIES AND TASKS**:

- Collaborate across the AstraZeneca Data and AI community to develop best practices and cross-functional opportunities that drive value
- Oversight of partnerships with multiple third parties, academic or outsourced partners to shape and drive project outcomes and knowledge building
- Own and lead Data Science & AI products per Cancer tumor type and /or Biopharma disease area. Product features include
- Development of ML Models & Classifiers for a deeper understanding of the patient journey
- Development of Predictive ML models around patient disease progression, Adverse events, and other outcomes
- Own and lead the development of ML models using unstructured notes, Scientific, Clinical documents, and Research publications
- Own and lead the development of Personalized ML models around the dissemination of Scientific, Medical content and messages across Physical & Digital Channels in a coordinated manner for the best patient outcomes
- Using domain-specific understanding, translate unstructured, complex business problems into the appropriate data problem, models, and analytical solutions across multiple disease areas
- Develop effective relationships with EU commercial and medical leaders to ensure the utilization and value of information resources

**YOUR EDUCATION & EXPERIENCE**

**Minimum Qualifications**:

- Bachelor’s Degree plus 5-7 years of progressive professional work experience in mathematics, computer science, engineering, physics, statistics, economics, computational sciences, or a quantitative discipline_.
- 7+ years of qualified professional experience can be substituted for Bachelor’s degree_
- Documented track record of Developing Data Science and AI products that have generated business value, and impact across multiple Industries
- In-depth experience with modern data science approaches, including unsupervised and supervised classification and regression algorithms such as k-means clustering, support vector machines, random forests, neural networks, and deep learning. May also have expertise in advanced statistical modeling or broader aspects of applied mathematics such as dynamic systems or optimization
- Advanced software development skills in at least two of the standard data science languages (such as R, Julia, or Python) and familiarity with database systems (e.g. SQL, NoSQL, graph)
- In-depth experience in manipulating and analyzing large high dimensionality unstructured datasets, drawing conclusions, defining recommended actions, and reporting results across stakeholders
- Excellent written and verbal communication, business analysis, and consultancy skills with stakeholders and colleagues

**Preferred Qualifications**:

- Advanced degree plus 3 - 5 years of progressive professional work experience in mathematics, computer science, engineering, physics, statistics, economics, or a quantitative discipline.
- Previous work experience in high-performance computing or cloud environment
- Documented track record of publishing relevant predictive modeling results and tools in peer-reviewed journals, conferences, and other scientific proceedings.
- Prior experience in understanding biomedical data sets and real-world data sets relevant to life sciences and healthcare
- Familiarity with navig

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