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The Asia Pacific Business Technology Team within Janssen Pharmaceuticals is looking for an extraordinary data scientist who is passionate about crafting, developing, and fielding data science solutions that drive impact for patients and for Janssen. There are many ways to explore and analyze data, and this powers the excitement and passion of data scientists at Janssen as many business units are eager to use the data to build business value.
Specifically, You Will
As the senior member of the Asia Pacific Region’s data science function and report to regional data science director, you will leverage your experience and communication skills to work across business teams to build and develop innovative data science models and algorithms. Your ability to communicate insights and influence decisions at various levels in the organization will be paramount to your success in this role. Focus areas include (but not limited) to patient/payer analytics, commercial strategy, and patient support program analytics.

• Lead and build data science projects by developing and applying creative solutions that go beyond current tools to deliver data-driven insights to high-priority scientific problems.
• Conceive, develop, and implement analytics solutions to high-priority scientific problems
• Participate in cross-functional collaborations with external companies and internal scientific and data science & analytics teams across the region.
• Shape internal/external collaborations and define the scope of data science questions.
• Clearly articulate highly technical methods and results to diverse audiences and partners to drive decision-making.

You will be someone who stays on the cutting edge of artificial intelligence, data science and advanced analytics research through novel project execution and development of algorithms that improve organizational performance and commercial effectiveness. The role requires both a broad knowledge of existing AI-type algorithms and the creativity to invent and customize when necessary. You will lead and work with matrixed teams across business and technology, and will be part of a dynamic, accomplished organization that will support multiple therapeutic areas.
Qualifications
Required Qualifications:

• Ph.D. with 6+ years of relevant experience, or M.S. with 8+ years of relevant experience, in Computer Sciences, Statistics, Machine Learning & Artificial Intelligence, Physics, Molecular Biology, Bioinformatics, Computational Informatics, Medical Informatics, Computational Biology or a related discipline.
• Experience leading highly matrixed teams and a proven track record of delivering high impact analytical projects.
• Strong working knowledge of machine learning platforms/environments.
• Strong working knowledge of AI-type algorithms, including machine learning techniques such as regression, decision trees, probability networks, association rules, clustering, neural networks, and/or Bayesian models.
• Familiarity with large datasets, handling of healthcare relevant datasets and understanding of data analysis workflows.
• Proficient with one or more programming language such as Python, R, SAS or Java.
• Strong working knowledge of common big data platforms / software development toolkits such as Kubernetes, AWS/Azure, Airflow, Jenkins, JIRA, Confluence, Git, Databrick. Familiar with the software development life cycle. Experience with deep learning framework, e,g. Tensorflow, PyTorch is a plus.
• Able to work in the interdisciplinary area and able to interpret and translate the very abstract and technical approaches to a healthcare and business relevant solution.
• Are a strong team player and you can work effectively in a collaborative, fast-paced, multi-tasking environment.
• Have excellent communication skills and a demonstrated ability to interact with different teams and parties of the organization, such as business, technical and academic partners.

Preferred Qualifications

• Experience in the commercial pharmaceuticals business.
• Experience with natural language processing in healthcare industry.
• Working knowledge of applicable healthcare and nonhealthcare data sets relevant to the ASPAC region.

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