Optimize and validate targeting mechanisms for specific health conditions Improve and optimize our proprietary contextualization, and recommendation engines that handle hundreds of thousands of transactions per second, billions of times each month Collaborate with internal Health experts to ideate and support rapid assessment, analysis, and prototyping of ideas for achievable commercialization.
What you will be tasked to do:
Research and develop user profiling models to enhance our clinical trial recommendation engine to leverage both online and offline data. Collaborate with Product teams on data-driven products to support clinical trial platform design and delivery. Support and enhance the existing work on health user profiling, prediction, and targeting tools. Contribute on future project on patient/physician identity for cross-device tracking, profiling and targeting. Support existing codebases for data integration and production support for our core models.
What you need to be successful in this role:
3+ years of full-time experience working as a Statistician/ Machine Learning Engineer/ Data Scientist Advanced knowledge of Big Data technologies such as Hadoop, Hive, and Impala Advanced knowledge of Python using the numpy/scipy/pandas/skilearn stack MS/PhD in Astronomy, Physics, Applied Mathematics, Statistics, Machine Learning, Computer Science; or BS with several years of applied machine learning experience
** All applicants must submit a code sample or a GitHub link to be considered ** Associated topics: application, c c++, developer, devops, java, perl, php, programming, sde, sw