Associate Director, Machine Learning (R1096146) in Beijing, China bei IQVIA™

Datum der Veröffentlichung 10/10/2019

Stellenauszug

  • Mitarbeiterkategorie:
    Vollzeitbeschäftigung
  • Jobkategorie:
  • Berufserfahrung:
    Not Specified
  • Datum der Veröffentlichung
    10/10/2019
  • Job ID:
    R1096146

Stellenbeschreibung

IQVIA™ is the leading human data science company focused on helping healthcare clients find unparalleled insights and better solutions for patients. Formed through the merger of IMS Health and Quintiles, IQVIA offers a broad range of solutions that harness the power of healthcare data, domain expertise, transformative technology, and advanced analytics to drive healthcare forward.

Machine Learning Scientist @ ACOE

Job Description

Join us on our exciting journey! IQVIA™ is the world's largest Human Data Science Company™, focused on using data and science to help healthcare clients find better solutions for their patients. Formed through the merger of IMS Health and Quintiles, IQVIA offers a broad range of solutions that harness advances in healthcare information, technology, analytics and human ingenuity to drive healthcare forward.

Machin Learning Team @ IQVIA, Analytics Center of Excellence

The machine learning team of IQVIA ACOE is led by Dr. Cao Xiao. Her research focuses on using machine learning approaches to solve diverse real world healthcare challenges, and has been published in leading AI conferences including KDD, NIPS, ICLR, AAAI, IJCAI, SDM, ICDM, WWW and top health informatics journals such as Nature Scientific Reports and JAMIA. Prior to IQVIA, she was a research staff member in the AI for Healthcare team at IBM Research from 2017 to 2019 and served as member of the IBM Global Technology Outlook Committee from 2018 to 2019.  She acquired her Ph.D. degree from University of Washington, Seattle in 2016.

The team is also in collaboration with Sunlab at Georgia Tech to work on exciting and impactful health data science projects as well as research publications for leading AI venues.

Machine Learning Scientist – the role

We're looking for machine learning scientists who are passionate about developing next generation machine learning technologies that will have profound impact on medicine and healthcare. Our ambitious machine learning for medicine and healthcare research agenda include but are not limited to

  • deep phenotyping integrating massive and multimodal health data
  • interpretable machine learning for disease prediction, subtyping and progression
  • pharmacovigilance, drug repurposing, and drug discovery from observational data using structured prediction, generative models, etc.
  • knowledge representation, distillation from multiple aspects of health data

As a machine learning scientist at IQVIA's ACOE, you get to work on the most cutting-edge and exciting projects. You will have access to petabytes of data, state of the art hardware such as massive distributed clusters and GPUs, and professional support from domain experts.

Your typical activities might include:

  • Implementing deep learning, machine learning, and data mining algorithms on distributed platform to solve real-world healthcare problems (e.g., disease prediction, risk prediction etc.)
  • Designing new algorithms to find predictive patterns that combine heterogeneous data assets, including electronic medical records, healthcare claims, clinical trial data, and unstructured text data.
  • Automating machine learning algorithms within the production environment.
  • Working with technology teams to support machine-learning algorithms in big data platforms. Supporting customized projects by designing and implementing algorithms and statistical models on related datasets.

Qualifications:

Our ideal candidate will have:

  • A PhD or master degree in computer science or related areas with research/publication in machine learning, artificial intelligence, data mining, natural language processing, etc. Candidates with strong publication records in top AI conferences is preferred.
  • An in-depth understanding of machine learning algorithms and modeling (supervised learning, semi-supervised or unsupervised learning including generative models, transfer learning, optimization, probabilistic graphical models, etc.)
  • In depth experience with Spark/Hadoop and either PyTorch/Tensorflow
  • Experience in Python with additional experience in Java, Scala and/or R.
  • Experience creating production environment data analytics and applications.

Join Us

Making a positive impact on human health takes insight, curiosity, and intellectual courage. It takes brave minds, pushing the boundaries to transform healthcare. Regardless of your role, you will have the opportunity to play an important part in helping our clients drive healthcare forward and ultimately improve outcomes for patients.

Forge a career with greater purpose, make an impact, and never stop learning.



Job ID: R1096146