Staff Machine Learning Scientist

• Formulate business problems as technical data problems while ensuring key business drivers are collected in collaboration product stakeholders.
• Work with product engineering to ensure implement-ability of solutions. Deliver prototypes and production code based on need.
• Experiment with in-house and third-party data sets to test hypotheses on relevance and value of data to business problems.
• Build needed data transformations on structured and un-structured data.
• Build and experiment with modeling and scoring algorithms. This includes development of custom algorithms as well as use of packaged tools based on machine learning, analytics, and statistical techniques.
• Devise and implement methods for adaptive learning with controls on efficiency, methods for explaining model decisions where vital, model validation, A/B testing of models.
• Devise and implement methods for efficiently monitoring model efficiency and performance in production.
• Devise and implement methods for automation of all parts of the predictive pipeline to minimize labor in development and production.
• Contribute to development and adoption of shared predictive analytics infrastructure.

Basic Qualifications:
8 or more years of work experience with a Bachelors Degree or with an Advanced Degree.
Relevant coursework in modeling techniques such as logistic regression, Na ve Bayes, SVM, decision trees, or neural networks.
Ability to program in one or more scripting languages such as Perl or Python and one or more programming languages such as Java, C++, or C#.
Experience with one or more common statistical tools such SAS, R, KNIME,.
Deep learning experience with TensorFlow is a plus.
Experience with Natural Language Processing is a plus.
Experience working with large datasets using tools like Hadoop, MapReduce, Pig, or Hive is a must.
Publications or presentation in recognized Machine Learning and Data Mining journals/conferences is a plus.