Staff Software Engineer - Data Science - Visa Business Solutions Products
- Austin, TX, USA
We dream of a future where it’s easy to pay and be paid. Across the planet. Where ever. Whenever. Securely. Easily.We have a great toolbox of leadership technologies including CyberSource and Authorize.net. Together, we are building leading edge full-service Payment Management solutions combining global payment processing, fraud management and payment security systems.
We are looking for a talented Senior Software Engineer to join our Enterprise Payments team!
Formulate business problems as technical data problems while ensuring key business drivers are captured in collaboration with Commercial product management.
Work with product development engineerings to ensure implement ability of solutions. Deliver prototypes and production code based on need.
Work with Data platform to drive availability of relevant data, tools, and infrastructure for group for experimental and development purposes.
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, data mining and statistical techniques.
Devise and implement methods for adaptive learning with controls on effectiveness, methods for explaining model decisions where necessary, model validation, A/B testing of models.
Devise and implement methods for efficiently monitoring model effectiveness 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
The responsibilities above are group responsibilities and specific individuals will be assigned responsibilities based on the group's needs and individual skills and preference Qualifications.
Recent graduate in PhD in Computer Science, Operations Research, Statistics or highly quantitative field (or equivalent experience) with strength in Deep Learning, Machine Learning, Data Mining, Statistical or other mathematical analysis.
Relevant coursework in modeling techniques such as logistic regression, Naïve Bayes, SVM, decision trees, or neural networks.
Deep learning experience with TensorFlow is a plus.
Strong understanding of algorithms and data structures.
Strong analytic and problem solving capability combined with ambition to solve real-world problems.
Results orientation with ability to plan work and work in a team
Experience working with large datasets using tools like Hadoop, MapReduce, Pig, or Hive is a plus.
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, Matlab.
Publications or presentation in recognized Machine Learning and Data Mining journals/conferences is a plus.
- You have strong apetitie to learn new technology and take on challenges
- You have strong verbal and written communication skills.
- You have excellent interpersonal skills and above all, you are team players!