Visa is looking to enhance its data capabilities by building out its data muscle, empowering teams to leverage data for smarter decisions, operational excellence, and innovation. The role aims to contribute to Visa's strategic vision as a world-leading data-driven company by delivering machine learning and AI solutions.
Requirements
- Relevant coursework in modeling techniques such as logistic regression, Naïve 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, MATLAB.
- 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, Spark, MapReduce, Pig, or Hive is a must.
- Publications or presentation in recognized Machine Learning and Data Mining journals/conferences is a plus.
Responsibilities
- Formulate business problems as technical data problems while ensuring key business drivers are collected in collaboration product stakeholders.
- Work with product and engineering to ensure effective 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 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.
Other
- This is a hybrid position. Hybrid employees can alternate time between both remote and office. Employees in hybrid roles are expected to work from the office 2-3 set days a week (determined by leadership/site), with a general guidepost of being in the office 50% or more of the time based on business needs.
- With a track record of successfully delivering complex software systems or services as Senior Data Scientist
- Proficiency working with agile methodologies, ceremonies.
- Exceptional collaboration and partnership skills with the ability to work in a global environment, drive consensus in cross-functional teams and comfortable operating in a matrix setup
- Demonstrated communications and interpersonal skills to interface well with diverse customer audience executives, product, and technology stakeholders.
