- Lead the regional machine learning engineers to deliver end to end machine learning solutions for our key projects across the region.
- Define the regional machine learning engineering strategy including people, technology, platforms and process.
- Collaborate with platform teams and solution architect to evolve our big data platforms and evaluate various data science technologies and services.
- 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 software engineering through novel project execution and development of algorithms that improve organizational performance and commercial effectiveness. The role requires both a broad knowledge of existing software development lifecycle, AI algorithms and the creativity to invent and customize when necessary. You will work with matrixed teams across business and technology, and will be part of a dynamic, accomplished organization that will support multiple therapeutic areas.
- M.S. with 5-6 years of experience, in Computer Sciences, Statistics, Machine Learning & Artificial Intelligence, Physics, Molecular Biology, Bioinformatics, Computational Informatics, Medical Informatics, Computational Biology or a related discipline.
- Minimum 4 years\' experience as a developer writing production code.
- Proven track record of building end to end machine learning pipelines and big data solutions.
- Strong programming skills in Python, proficiency in Spark is preferred.
- Strong working knowledge of common big data platforms / software development toolkits such as Kubernetes, AWS/Azure, Airflow, Jenkins, JIRA, Confluence, Git, Databricks. Familiar with the software development life cycle. Experience with deep learning framework, e,g. Tensorflow, PyTorch is a plus.
- 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.
- Experience of leading and managing an engineering team is preferred.
- 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.
- Experience in technology, FMCG, internet companyoh, healthcare industry is preferred eQuest
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Manager, Machine Learning Engineering - Singapore - Johnson & Johnson
Description
The APAC Business Technology Team within Janssen Pharmaceuticals is looking for an extraordinary machine learning engineer who is passionate about crafting, developing, and fielding data science solutions that drive impact for HCP (Health Care Professional), 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 regional leader for machine learning engineering, you will be responsible for building and leading the machine learning engineering capability across the region. You will leverage your experience and communication skills to work across business & technology teams to build and develop innovative data science models and algorithms. Your technical knowledge and ability to apply them to in Janssen 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. Specifically, you will lead and build end-to-end machine learning pipelines by developing and applying creative solutions that go beyond current tools and work together with data scientist to build predictive models.
